Chemical/instrumental approaches to the evaluation of wine chemistry

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Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties

In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set

Headspace solid-phase microextraction combined with mass spectrometry as a powerful analytical tool for profiling the terpenoid metabolomic pattern of hop-essential oil derived from Saaz variety

Hop(HumuluslupulusL.,Cannabaceaefamily)isprizedforitsessentialoilcontents,usedin beer production and, more recently, in biological and pharmacological applications. In this work,a methodinvolvingheadspace solid-phase microextractionand gas chromatography– mass spectrometry was developed and optimized to establish the terpenoid (monoterpenes and sesquiterpenes) metabolomic pattern of hop-essential oil derived from Saaz variety as a mean to explore this matrix as a powerful biological source for newer, more selective, biodegradable and naturally produced antimicrobial and antioxidant compounds. Different parameters affecting terpenoid metabolites extraction by headspace solid-phase microextraction were considered and optimized: type of fiber coatings, extraction temperature, extraction time, ionic strength, and sample agitation. In the optimized method, analytes were extracted for 30 min at 40 C in the sample headspace with a 50/30 m divinylbenzene/carboxen/polydimethylsiloxane coating fiber. The methodology allowed the identification of a total of 27 terpenoid metabolites, representing 92.5% of the total Saaz hop-essential oil volatile terpenoid composition. The headspace composition was dominated by monoterpenes (56.1%, 13 compounds), sesquiterpenes (34.9%, 10), oxygenated monoterpenes (1.41%, 3), and hemiterpenes (0.04%, 1) some of which can probably contribute to the hop of Saaz variety aroma. Mass spectrometry analysis revealed that the main metabolites are the monoterpene -myrcene (53.0±1.1% of the total volatile fraction), and the cyclic sesquiterpenes, -humulene (16.6 ± 0.8%), and -caryophyllene (14.7 ± 0.4%), which together represent about 80% of the total volatile fraction from the hop-essential oil. Thesefindingssuggestthatthismatrixcanbeexploredasapowerfulbiosourceofterpenoid metabolites

Dynamic headspace solid-phase microextraction combined with one-dimensional gas chromatography–mass spectrometry as a powerful tool to differentiate banana cultivars based on their volatile metabolite profile

In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography–mass spectrometry (1D-GC–qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure

Madeira wine volatile profile. A platform to establish madeira wine aroma descriptors

In the present study we aimed to investigate the volatile organic compounds (VOCs) that may potentially be responsible for specific descriptors of Madeira wine providing details about Madeira wine aroma notes at molecular level. Moreover, the wine aroma profile, based on the obtained data, will be a starting point to evaluate the impact of grape variety (Malvasia, Bual, Sercial, Verdelho and Tinta Negra), type (sweet, medium sweet, dry and medium dry), and age (from 3 to 20 years old) on Madeira wine sensorial properties. Firstly, a comprehensive and in-depth Madeira wine volatile profiling was carried out using headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS–SPME/GC–qMS). Secondly, a relation among the varietal, fermentative and aging aroma compounds, and their aroma descriptors with the Madeira wine sensorial properties was assessed. A total of 82 VOCs, belonging to different chemical families were identified, namely 21 esters, 13 higher alcohols, ten terpenic compounds, nine fatty acids, seven furanic compounds, seven norisoprenoids, six lactones, four acetals, four volatile phenols and one sulphur compound. From a sensorial point of view, during the aging process the wine lost its freshness and fruitiness odor related to the presence of some varietal and fermentative compounds, whereas other descriptors such as caramel, dried fruits, spicy, toasty and woody, arose during ageing. The Maillard reaction and diffusion from the oak were the most important pathways related with these descriptors. A relationship-based approach was used to explore the impact of grape variety, wine type, and age on Madeira wine sensorial properties based on shared number of VOCs and their odors.info:eu-repo/semantics/publishedVersio

Valorization of Spent Coffee Grounds as a Natural Source of Bioactive Compounds for Several Industrial Application: A Volatilomic Approach

Coffee is one of the most popular beverages worldwide, whose production and consump tion result in large amounts of waste, namely spent coffee grounds, constituting an important source of compounds for several industrial applications. This work focused on the establishment of the volatile fingerprint of five spent coffee grounds from different geographical origins using headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME/GC MS), as a strategy to identify volatile organic metabolites (VOMs) with potential application in the food industry as antioxidant, anti-inflammatory, and antiproliferative agents. One hundred eleven VOMs belonging to different chemical families were identified, of which 60 were found in all spent coffee grounds analyzed. Furanic compounds (34%), nitrogen compounds (30%), and esters (19%) contributed significant to the total volatile fingerprint. The data obtained suggest that spent coffee grounds have great potential to be used as raw material for different approaches in the food industry towards the development of new food ingredients or products for human consumption, in addi tion to pharmaceutical and cosmetic applications, namely as antioxidant (e.g., limonene, carvacrol), antimicrobial (e.g., pyrrole-2-carboxaldehyde, β-myrcene) and anti-inflammatory (e.g., furfural, 2- furanmethanol) agents, promoting their integral valorization within the circular bioeconomy concept.info:eu-repo/semantics/publishedVersio

Recent Developments in the Applications of Fingerprinting Technology in the Food Field

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A high-throughput analytical strategy based on QuEChERS-dSPE/HPLC–DAD–ESI-MSn to establish the phenolic profile of tropical fruits

Tropical fruits are a rich source of phenolic compounds which are favorable in defending the human body against damage induced by free radicals (e.g., ROS, RNS). In the current work, a high throughput analytical approach based on a simple extraction procedure (QuEChERS-dSPE) combined with high-performance liquid chromatography-diode array detector-electrospray ionization-mass spectrometry (HPLC-DAD-ESI-MSn ) was used to establish the phenolic profile of tropical fruits. The proposed method showed good linearity (r2 ≥ 0.991), precision (RSD < 8 %), as well as low limits of detection (LOD ≤ 19.7 μg/L) and quantification (LOQ ≤ 65.8 μg/ L). Thirty-four phenolic compounds were identified as belonging to different chemical groups, from which only 6 were common to all tropical fruits. Pitanga showed the highest relative phenolic concentration (99.5 mg/100 g of fruit), with the passion fruit (17.5 mg/100 g of fruit) the lowest. Flavonols were the most predominant chemical group in tropical fruits, representing 77.9, 60.1, and 55.8% of the phenolic composition of pitanga, passion fruit and mango, respectively. The data obtained allow deep and comprehensive insights into the phenolic compo sition of tropical fruits in order to explore its potential bioactive activity. Nevertheless, in vivo assays using fruit extracts will be essential to recognize their potential health-promoting properties.info:eu-repo/semantics/publishedVersio

A new and improved strategy combining a dispersive-solid phase extraction-based multiclass method with ultra high pressure liquid chromatography for analysis of low molecular weight polyphenols in vegetables

This paper reports on the development and optimization of a modified Quick, Easy, Cheap Effective, Rugged and Safe (QuEChERS) based extraction technique coupled with a clean-up dispersive-solid phase extraction (dSPE) as a new, reliable and powerful strategy to enhance the extraction efficiency of free low molecular-weight polyphenols in selected species of dietary vegetables. The process involves two simple steps. First, the homogenized samples are extracted and partitioned using an organic solvent and salt solution. Then, the supernatant is further extracted and cleaned using a dSPE technique. Final clear extracts of vegetables were concentrated under vacuum to near dryness and taken up into initial mobile phase (0.1% formic acid and 20% methanol). The separation and quantification of free low molecular weight polyphenols from the vegetable extracts was achieved by ultrahigh pressure liquid chromatography (UHPLC) equipped with a phodiode array (PDA) detection system and a Trifunctional High Strength Silica capillary analytical column (HSS T3), specially designed for polar compounds. The performance of the method was assessed by studying the selectivity, linear dynamic range, the limit of detection (LOD) and limit of quantification (LOQ), precision, trueness, and matrix effects. The validation parameters of the method showed satisfactory figures of merit. Good linearity (View the MathML sourceRvalues2>0.954; (+)-catechin in carrot samples) was achieved at the studied concentration range. Reproducibility was better than 3%. Consistent recoveries of polyphenols ranging from 78.4 to 99.9% were observed when all target vegetable samples were spiked at two concentration levels, with relative standard deviations (RSDs, n = 5) lower than 2.9%. The LODs and the LOQs ranged from 0.005 μg mL−1 (trans-resveratrol, carrot) to 0.62 μg mL−1 (syringic acid, garlic) and from 0.016 μg mL−1 (trans-resveratrol, carrot) to 0.87 μg mL−1 ((+)-catechin, carrot) depending on the compound. The method was applied for studying the occurrence of free low molecular weight polyphenols in eight selected dietary vegetables (broccoli, tomato, carrot, garlic, onion, red pepper, green pepper and beetroot), providing a valuable and promising tool for food quality evaluation

Quality Index Method for fish quality control: Understanding the applications, the appointed limits and the upcoming trends

Background: The Quality Index Method (QIM) is a widely used approach for fish sensory grading, based on a structured scaling for freshness measurements, providing information concerning the fish freshness status, as a prediction of the remaining shelf-life for specific species or products. However, its tendency to be used in an oversimplified way and other common misapplications could lead to discredit of a methodology with great potential. Scope and approach: Review the principles of QIM methodology, discussing its concept, applications, and un derstand their limits, as a useful strategy to propose improvements, reinforce its predictive power and consequent acceptability. Key findings and conclusions: QIM methodology is based on a compromise between the number of fish samples necessary and the number of attributes, with sensory relevance in fish spoilage, that allows verifying if quality requirements are fulfilled. However, the assumptions inherent to the method, undermine the reliability of the shelf-life predictions. Determination of the variability associated with assessors, product, and correct structure of datasets for statistical analysis, will improve the predictive power of the method. However, it could lead to an increase in the method complexity that would drive it away from the industry’s needs for fast and easily implemented methods.info:eu-repo/semantics/publishedVersio