Alexis Marsol-Vall

Ultra performance liquid chromatography analysis to study the changes in the carotenoid profile of commercial monovarietal fruit juices

We have developed an analytical method that allows the simultaneous determination of epoxycarotenoids, hydroxycarotenoids and carotenes in monovarietal fresh homemade and industrially processed fruit products. Analyses were carried out using ultra performance liquid chromatography (UPLC). The extraction method was optimized using methanol as the first extraction solvent for lyophilized samples followed by a saponification step. Recoveries ranged between 75% and 104% depending on the compound. Repeatability was better than 10% for all compounds (%RSD, n=3). The chromatographic analysis takes less than 17min. In this short period, up to 27 carotenoids were identified in apple, peach and pear products. The developed method allowed us to differentiate juice from six varieties of apple by their carotenoid profile. Moreover, the methodology allows us to differentiate the carotenoid profiles from commercial juices and homemade fresh peach and pear juices, as well as to study the rearrangements of 5,6- to 5,8-epoxycarotenoids.

Dispersive liquid–liquid microextraction and injection-port derivatization for the determination of free lipophilic compounds in fruit juices by gas chromatography-mass spectrometry

A method consisting of dispersive liquid-liquid microextraction (DLLME) followed by injection-port derivatization and gas chromatography-mass spectrometry (GC-MS) for the analysis of free lipophilic compounds in fruit juices is described. The method allows the analysis of several classes of lipophilic compounds, such as fatty acids, fatty alcohols, phytosterols and triterpenes. The chromatographic separation of the compounds was achieved in a chromatographic run of 25.5min. The best conditions for the dispersive liquid-liquid microextraction were 100μL of CHCl3 in 1mL of acetone. For the injection-port derivatization, the best conditions were at 280°C, 1min purge-off, and a 1:1 sample:derivatization reagent ratio (v/v) using N-methyl-N-(trimethylsilyl)trifluoroacetamide (MSTFA):pyridine (1:1) as reagent. Quality parameters were assessed for the target compounds, giving a limits of detection (LODs) ranging from 1.1 to 5.7ng/mL and limits of quantification (LOQs) from 3.4 to 18.7ng/mL for linoleic and stearic acid, respectively. Repeatability (%RSD, n=5) was below 11.51% in all cases. In addition, the method linearity presented an r2 ≥0.990 for all ranges applied. Finally, the method was used to test the lipophilic fraction of various samples of commercial fruit juice.

A rapid gas chromatographic injection-port derivatization method for the tandem mass spectrometric determination of patulin and 5-hydroxymethylfurfural in fruit juices.

A novel method consisting of injection-port derivatization coupled to gas chromatography-tandem mass spectrometry is described. The method allows the rapid assessment of 5-hydroxymethylfurfural (HMF) and patulin content in apple and pear derivatives. The chromatographic separation of the compounds was achieved in a short chromatographic run (12.2min) suitable for routine controls of these compounds in the fruit juice industry. The optimal conditions for the injection-port derivatization were at 270°C, 0.5min purge-off, and a 1:2 sample:derivatization reagent ratio (v/v). These conditions represent an important saving in terms of derivatization reagent consumption and sample preparation time. Quality parameters were assessed for the target compounds, giving LOD of 0.7 and 1.6μg/kg and LOQ of 2 and 5μg/kg for patulin and HMF, respectively. These values are below the maximum patulin concentration in food products intended for infants and young children. Repeatability (%RSD n=5) was below 12% for both compounds. In addition, the method linearity ranged between 25 and 1000μg/kg and between 5 and 192μg/kg for HMF and patulin, respectively. Finally, the method was applied to study HMF and patulin content in various fruit juice samples.

Injection-port derivatization coupled to GC–MS/MS for the analysis of glycosylated and non-glycosylated polyphenols in fruit samples

Polyphenols, including glycosylated polyphenols, were analyzed via a procedure based on injection-port derivatization coupled to gas chromatography-tandem mass spectrometry (GC-MS/MS). The polyphenols in lyophilized fruit samples were extracted with an acidified MeOH mixture assisted by ultrasound. Samples were dried under vacuum, and carbonyl groups were protected with methoxylamine. Free hydroxyl groups were subsequently silylated in-port. Mass fragmentations of 17 polyphenol and glycosylated polyphenol standards were examined using Multiple Reaction Monitoring (MRM) as the acquisition mode. Furthermore, in-port derivatization was optimized in terms of optimal injection port temperature, derivatization time and sample: N-methyl-N-(trimethylsilyl)trifluoroacetamide (MSTFA) volume ratio. A C18 solid-phase-extraction clean-up method was used to reduce matrix effects and injection liner degradation. Using this clean-up method, recoveries for samples spiked at 1 and 10μg/g ranged from 52% to 98%, depending on the chemical compound. Finally, the method was applied to real fruit samples containing the target compounds. The complete chromatographic runtime was 15min, which is faster than reported for recent HPLC methods able to analyze similar compounds.

Development of a SBSE-TD method coupled to GC–MS and chemometrics for the differentiation of variety and processing conditions in peach juices

Peach juices of distinct varieties, namely yellow- and red-fleshed, and commercial and freshly blended were analyzed. The method used was based on Stir Bar Sorptive Extraction (SBSE) involving a polydimethylsiloxane-coated stir bar with thermal desorption (TD), followed by gas chromatography coupled to mass spectrometry (GC-MS) analysis. The resulting analytical data included 41 compounds belonging to several chemical classes, such as aldehydes, alcohols, lactones, terpenoids, fatty aldehydes, fatty acids and hydrocarbons. Furthermore, chemometric data treatment using unsupervised analysis (PCA) proved useful to classify peach juices on the basis of variety. Stepwise Linear Discriminant Analysis (SLDA) showed that a reduced number of variables (14 compounds), including lactones (6-pentyl-α-pyrone, γ-decalactone, γ-dodecalactone, and δ-dodecalactone), fatty acids (hexadecanoic acid), fatty aldehydes (tetracosanal and octacosanal), hydrocarbons (C23, C26, C27, C29, and C33), and alcohols (phytol and α-tocopherol), were necessary to classify the juice samples according to variety and processing conditions.

Profiles of Volatile Compounds in Blackcurrant (Ribes nigrum) Cultivars with a Special Focus on the Influence of Growth Latitude and Weather Conditions

The volatile profiles of three blackcurrant (Ribes nigrum L.) cultivars grown in Finland and their responses to growth latitude and weather conditions were studied over an 8 year period by headspace solid-phase microextraction (HS-SPME) followed by gas-chromatographic–mass-spectrometric (GC-MS) analysis. Monoterpene hydrocarbons and oxygenated monoterpenes were the major classes of volatiles. The cultivar ‘Melalahti’ presented lower contents of volatiles compared with ‘Ola’ and ‘Mortti’, which showed very similar compositions. Higher contents of volatiles were found in berries cultivated at the higher latitude (66° 34′ N) than in those from the southern location (60° 23′ N). Among the meteorological variables, radiation and temperature during the last month before harvest were negatively linked with the volatile content. Storage time had a negative impact on the amount of blackcurrant volatiles.

Bulk industrial fruit fibres. Characterization and prevalence of the original fruit metabolites

Here we analysed the content of primary and secondary metabolites in nine types of industrially processed fibres derived from the juice industry. Specifically, we examined fibre from: apple, peach, and pear, as non-citrus fruits; the peel and flesh of orange and tangerine, and lemon flesh, as citrus fruits; and carrot, as vegetable. Regarding primary metabolites, the sugar content ranged from 21.6 mg/g in lemon to 290 mg/g in orange peel and lower mass organic acid content ranged from 25.0 mg/g in pear to 250 mg/g in lemon. The content of fatty acids were constant during fibre processing, ranging from 0.5 to 1.46%. Furthermore, the fatty acid profile was not affect for the processing. Concerning secondary metabolites, industrial processing did not decrease the sterols content, which ranged from 0.51 to 1.66 μg/g. Regarding carotenoids, of note was the presence of epoxycarotenoids, which may reflect the quality of the industrial process, thus giving added value to the by-product.

Volatile Composition and Enantioselective Analysis of Chiral Terpenoids of Nine Fruit and Vegetable Fibres Resulting from Juice Industry By-Products

Fruit and vegetable fibres resulting as by-products of the fruit juice industry have won popularity because they can be valorised as food ingredients. In this regard, bioactive compounds have already been studied but little attention has been paid to their remaining volatiles. Considering all the samples, 57 volatiles were identified. Composition greatly differed between citrus and noncitrus fibres. The former presented over 90% of terpenoids, with limonene being the most abundant and ranging from 52.7% in lemon to 94.0% in tangerine flesh. Noncitrus fibres showed more variable compositions, with the predominant classes being aldehydes in apple (57.5%) and peach (69.7%), esters (54.0%) in pear, and terpenoids (35.3%) in carrot fibres. In addition, enantioselective analysis of some of the chiral terpenoids present in the fibre revealed that the enantiomeric ratio for selected compounds was similar to the corresponding volatile composition of raw fruits and vegetables and some derivatives, with the exception of terpinen-4-ol and α-terpineol, which showed variation, probably due to the drying process. The processing to which fruit residues were submitted produced fibres with low volatile content for noncitrus products. Otherwise, citrus fibres analysed still presented a high volatile composition when compared with noncitrus ones.

Comprehensive Two-dimensional Gas Chromatography Time-of-flight Mass Spectrometry to Assess the Presence of α,α-Trehalose and Other Disaccharides in Apple and Peach

INTRODUCTION Carbohydrates are important constituents in fruits. Among the carbohydrates, disaccharides have rarely been studied in apple and peach. Indeed, the abiotic stress biomarker and preservation agent α,α-trehalose is a disaccharide. OBJECTIVES To establish a comprehensive method based on two-dimensional gas chromatography combined with time-of-flight MS detection (GC × GC-ToF/MS) to analyse the disaccharide composition of apple and peach. METHODS The sample preparation was based on aqueous-methanolic extraction of the analytes, followed by oxime formation and trimethylsilylation of the disaccharides. First, three columns were tested with standards on the one-dimensional system. Next, to perform the sample analysis using GC × GC-MS (which offers significant advantages over conventional GC because it allows higher separation efficiencies), various column configurations were assessed on the two-dimensional system to obtain enhanced separation and low detection limits. The column sets tested included non-polar/semi-polar, semi-polar/polar and polar/non-polar. RESULTS Using the method that proved to be more efficient, namely the method developed with the semi-polar/non-polar configuration, ten disaccharides were identified, based on analytical standards, retention index and mass spectra. These compounds were quantified in several varieties of apple and peach fruit using the developed GC × GC method and linear curve calibration, resulting in substantial differences among the fruits. However, cultivars within the fruits exhibited no significant differences. CONCLUSION The proposed method allowed for the identification and quantification of several disaccharides in apple and peach, including the biomarker α,α-trehalose.