Analysis of polyphenols in wines: Correlation between total polyphenolic content and antioxidant potential from photometric measurements

Chemical fingerprinting of phenolic compounds in Finnish berry wines using Fourier transform ion cyclotron resonance mass spectrometry

Chemical fingerprinting of phenolic compounds present in Finnish berry wines was performed using a direct-infusion Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). The main aim of this study was to compare the phenolics profiles of wines produced from natural and/or cultivated berries and to demonstrate the feasibility of FT-ICR MS for a direct chemical analysis of the wine samples without chromatographic separation. First, phenolic compounds were recovered from the wine samples by solid-phase extraction (SPE), and the total phenolic content (TPC) was then determined by a Folin-Ciocalteau assay. The TPC of the original berry wines varied from 421 to 2108 mg/L, while the TPC of the extracts was 157-1525 mg/L. Over fifty phenolic compounds were tentatively identified from the wine samples by FT-ICR MS, whose concentrations highly varied depending on the types of berries used in the winemaking process.

Simultaneous Determination of Fifteen Polyphenols in Fruit Juice Using Ultrahigh-Performance Liquid Chromatography-Tandem Mass Spectrometry Combining Dispersive Liquid-Liquid Microextraction

Polyphenols are secondary metabolites of plants and used as effective antioxidants in dietary supplements, whose main sources are fruits, vegetables, and grains. To clarify the content and distribution of polyphenols in different fruit species samples accurately, a rapid and sensitive ultrahigh-pressure liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS) method combining dispersive liquid-liquid microextraction (DLLME) was developed for quantitative determination of fifteen polyphenol compounds in fruit juice. In this method, the targets were first extracted from 1 g of fruit juice sample using 10 mL of 80% ethanol solution by ultrasonic-assisted extraction (UAE). Then, 1.0 mL of UAE extracted solution, 60 μL of n-octanol and 2.0 mL of H₂O were performed in the following DLLME procedure. A C₁₈ reversed-phase column, ZORBAX SB (100 × 4.6 mm, 3.5 μm), was proposed under gradient elution with 0.1% formic acid aqueous solution and methanol mobile phases for the determination of 15 polyphenols, allowing us to obtain polyphenolic profiles in less than 23.0 min. Under the optimum conditions, the enrichment factors ranged from 162 to 194. The results showed that the 15 polyphenols had linear correlation coefficients (R²) more than 0.99. The limits of detection (LODs) were between 18.3 and 103.5 ng/g, and the average recoveries were between 96.9 and 116.3% with interday relative standard deviations (RSDs) ranging from 4.4 to 8.2% in all cases. The method was successfully applied to the analysis of real fruit juice samples and presented itself as a simple, rapid, practical, and environment-friendly technique.

The Content of Selected Bioactive Compounds in Wines Produced from Dehydrated Grapes of the Hybrid Variety ‘Hibernal’ as a Factor Determining the Method of Producing Straw Wines

Sweet wines are appreciated worldwide; many are produced by fermenting the must of dehydrated (semi-dried) grapes, using methods that vary from region to region. The aim of this study was to evaluate the basic chemical and oenological characteristics of wines obtained by three technologies of production. The wines were made from a hybrid cultivar ‘Hibernal’, grown under cool climate conditions. ‘Hibernal’ is a hybrid variety. This ‘Hibernal’ variety is widely cultivated in central and eastern Europe, where it is of great economic importance. Wines produced from this variety are popular in local markets. In comparison with the production of varieties belonging to Vitis vinifera, a very small percentage of the ‘Hibernal’ variety is cultivated. The methods used in the experiment for the production of wines were: classical method in the Italian passito style, modification of the passito style with a seven-day maceration of grapes, and a method of production in the Tokaj wine style at five Puttonyos. Basic chemical parameters, acid profile, total phenolic content, antioxidant and antiradical capacities, and quantitative analysis of selected polyphenols was performed. The sensory features and quality of the wines was assessed using a sommelier analysis based on The Wine & Spirit Education Trust guidelines. The results indicated that the seven-day maceration of the dehydrated grapes resulted in the highest polyphenol content, as well as the largest antioxidant and antiradical contents. The oenological evaluation of wines produced by the Tokaj method and Italian passito method with seven-day maceration found that the wines were appreciated due to their rich taste, flavor, and overall quality. The present study confirms the promising opportunities to obtain special sweet wine with a valuable composition and oenological characteristics in regions with cooler climates.

A critical review on the applications of artificial neural networks in winemaking technology

Since their development in 1943, artificial neural networks were extended into applications in many fields. Last twenty years have brought their introduction into winery, where they were applied following four basic purposes: authenticity assurance systems, electronic sensory devices, production optimization methods, and artificial vision in image treatment tools, with successful and promising results. This work reviews the most significant approaches for neural networks in winemaking technologies with the aim of producing a clear and useful review document.

A novel and simple cell-based electrochemical biosensor for evaluating the antioxidant capacity of Lactobacillus plantarum strains isolated from Chinese dry-cured ham

The analysis of antioxidants in foodstuffs has become an active area of research, leading to the recent development of numerous methods for assessing antioxidant capacity. Here we described the fabrication and validation of a novel and simple cell-based electrochemical biosensor for this purpose. The biosensor is used to assess the antioxidant capacity of cell-free extracts from Lactobacillus plantarum strains isolated from Chinese dry-cured ham. The biosensor relies on the determination of cellular reactive oxygen species (ROS) (the flux of H₂O₂ released from RAW 264.7 macrophage cells) to indirectly assess changes in intracellular oxidative stress level as influenced by L. plantarum strains. A one-step acidified manganese dioxide (a-MnO₂) modified gold electrode (GE) was used to immobilize RAW 264.7 macrophage cells, which were then encapsulated in a 3D cell culture system consisting of alginate/ graphene oxide (NaAlg/GO). The biosensor exhibited a rapid and sensitive response for the detection of H₂O₂ released from RAW264.7 cells. The detection limit was 0.02μM with a linear response from 0.05μM to 0.85μM and the biosensor was shown to have good stability and outstanding repeatability. This technique was then used for evaluating the antioxidant ability of extracts from L. plantarum NJAU-01. According to the electrochemical investigations and assays of SEM, TEM, and ROS, these cell-free extracts effectively reduced the oxidative stress levels in RAW264.7 cells under external stimulation. Extracts from L. plantarum strains at a dose of 10¹⁰CFU/mL showed the highest antioxidant activities with a relative antioxidant capacity (RAC) rate of 88.94%. Hence, this work provides a simple and efficient electrochemical biosensing platform based on RAW264.7 cells for fast, sensitive and quantitative assessment of antioxidant capacity of L. plantarum strains. The method demonstrates its potential for rapid screening for evaluating antioxidant properties of samples.

Trace determination of safranin O dye using ultrasound assisted dispersive solid-phase micro extraction: Artificial neural network-genetic algorithm and response surface methodology

In this study, ultrasound assisted dispersive solid-phase micro extraction combined with spectrophotometry (USA-DSPME-UV) method based on activated carbon modified with Fe2O3 nanoparticles (Fe2O3-NPs-AC) was developed for pre-concentration and determination of safranin O (SO). It is known that the efficiency of USA-DSPME-UV method may be affected by pH, amount of adsorbent, ultrasound time and eluent volume and the extent and magnitude of their contribution on response (in term of main and interaction part) was studied by using central composite design (CCD) and artificial neural network-genetic algorithms (ANN-GA). Accordingly by adjustment of experimental conditions suggested by ANN-GA at pH 6.5, 1.1mg of adsorbent, 10min ultrasound and 150μL of eluent volume led to achievement of best operation performance like low LOD (6.3ngmL(-1)) and LOQ (17.5ngmL(-1)) in the range of 25-3500ngmL(-1). In following stage, the SO content in real water and wastewater samples with recoveries between 93.27-99.41% with RSD lower than 3% was successfully determined.

Analysis of phenolic compounds in commercial dried grape pomace by high-performance liquid chromatography electrospray ionization mass spectrometry

By-products obtained from winemaking processes still contain large amounts of phenolic compounds, especially phenolic acids, flavanols, flavonols, stilbenes, and flavonoids. Enzymatic hydrolysis was used for determination and characterization of phenolic acids, flavanols, flavonols, and stilbenes. Characterization of the flavonoids was achieved using acid hydrolysis with 0.1% hydrochloric acid. In addition, organic solvents as 50% methanol, 70% methanol, 50% acetone, 0.01% pectinase, and 100% petroleum ether were also evaluated. Reversed phase high-performance liquid chromatography (RP-HPLC) with diode array detector was used to identify phenolic compounds. Internal standard quantification was implemented using a five points of the UV-visible absorption data collected at the wavelength of maximum absorbance. A total of 16 phenolic compounds were determined. The content differed from 1.19 to 1124 mg kg⁻¹. Outcomes from HPLC study showed that gallic acid, (+) catechin hydrate, and (−) epicatechin gallate were the major phenolic compounds presented in the sample. Malvidin and pelargonidin 3-O-glucoside were the major anthocyanins monoglucosides.

Biosorption of cobalt(II) with sunflower biomass from aqueous solutions in a fixed bed column and neural networks modelling

The effects of inlet cobalt(II) concentration (20-60 ppm), feed flow rate (8-19 ml/min) and bed height (5-15 cm), initial solution pH (3-5) and particle size (0.25<x<0.5, 0.5<x<1 and 1<x<2 mm) on the breakthrough curves were investigated. The highest bed capacity of 11.68 mg/g was obtained using 40 ppm inlet cobalt(II) concentration, 5 cm bed height and 8 ml/min flow rate, pH 6.5 and 0.25<x<0.5 mm particle size. According to the BET (N2) measurements, the specific surface area of the shells of sunflower biomass was found to be 1.82 m(2)/g. A relationship between the predicted results of the ANN model and experimental data was conducted. The ANN model yielded determination coefficient of (R(2) 0.972), standard deviation ratio (0.166), mean absolute error (0.0158) and root mean square error (0.0141). The results indicated that the shells of the sunflower biomass is a suitable biosorbent for the uptake of cobalt(II) in fixed bed columns.

Analytical characterization of wine and its precursors by capillary electrophoresis

The accurate determination of marker chemical species in grape, musts, and wines presents a unique analytical challenge with high impact on diverse areas of knowledge such as health, plant physiology, and economy. Capillary electromigration techniques have emerged as a powerful tool, allowing the separation and identification of highly polar compounds that cannot be easily separated by traditional HPLC methods, providing complementary information and permitting the simultaneous analysis of analytes with different nature in a single run. The main advantage of CE over traditional methods for wine analysis is that in most cases samples require no treatment other than filtration. The purpose of this article is to present a revision on capillary electromigration methods applied to the analysis of wine and its precursors over the last decade. The current state of the art of the topic is evaluated, with special emphasis on the natural compounds that have allowed wine to be considered as a functional food. The most representative revised compounds are phenolic compounds, amino acids, proteins, elemental species, mycotoxins, and organic acids. Finally, a discussion on future trends of the role of capillary electrophoresis in the field of analytical characterization of wines for routine analysis, wine classification, as well as multidisciplinary aspects of the so-called "from soil to glass" chain is presented.

Antioxidant activity prediction and classification of some teas using artificial neural networks

In order to characterise and to classify some teas a simple, rapid and economical method based on composition, antioxidant activity and artificial neural networks (ANNs) is proposed. For these purpose two types of ANN based applications have been developed: one for predicting the antioxidant activity and a second one for establishing the class of the teas. The complex relationship between the total antioxidant activity (AA) depending on the total flavonoids content (F), total catechins content (C) and total methyl-xanthines content (MX) of commercial teas was revealed by the first designed feed-forward ANN. Secondly, using a probabilistic ANN, successful tea classification in various classes (green tea, black tea and express black tea) was also performed.

A study of the extraction kinetics of the minerals from the white lady's bedstraw (Galium mollugo L.) by using an artificial neural network

The present work deals with the mineral composition of the extracts obtained from lady's bedstraw (Galium mollugo L.) by maceration, extraction under reflux (extraction at the boiling temperature of solvent) and ultrasonic extraction, using atomic absorption spectrometry. The main goals of the work were to evaluate the operation of an artificial neural network (ANN) of the selected topology, to determine the parameters of a kinetic model of unsteady diffusion of minerals through plant material, and to define the yield of minerals as a function of the time of extraction and the yield of total extract (resinoid). The ANN results showed a positive correlation with the experimental data, so they could be used to examine the kinetics of extraction of minerals from lady's bedstraw (G. mollugo), regardless of the extraction technique. The yield of minerals (K, Ca and Mg) was correlated with the time of extraction and the yield resinoid by a polynomial equation of the first order in both variables.

Cluster analysis and artificial neural networks multivariate classification of onion varieties

Eight cultivars of different colored onions (white, golden, and red) were evaluated for fresh bulbs cultivated and grown under the same environmental and agronomical conditions. Cluster analysis and principal component analysis, based on different flavonoids, total phenols, and pungency, data showed that the onions were not clustered according to variety (genetic similarity degree), whereas the color was the variable with the highest influence, ranging between 50 and 70%. Artificial neural networks were applied to study the possibility of discriminating among onion varieties. Characterization of the onion according to variety and procedence of the seeds was around 95-100%. Samples belonging to the Carrizal Alto procedence had an incorrect classification for 25% of the data.

Application and potential of capillary electroseparation methods to determine antioxidant phenolic compounds from plant food material

Antioxidants are one of the most common active ingredients of nutritionally functional foods which can play an important role in the prevention of oxidation and cellular damage inhibiting or delaying the oxidative processes. In recent years there has been an increased interest in the application of antioxidants to medical treatment as information is constantly gathered linking the development of human diseases to oxidative stress. Within antioxidants, phenolic molecules are an important category of compounds, commonly present in a wide variety of plant food materials. Their correct determination is pivotal nowadays and involves their extraction from the sample, analytical separation, identification, quantification and interpretation of the data. The aim of this review is to provide an overview about all the necessary steps of any analytical procedure to achieve the determination of phenolic compounds from plant matrices, paying particular attention to the application and potential of capillary electroseparation methods. Since it is quite complicated to establish a classification of plant food material, and to structure the current review, we will group the different matrices as follows: fruits, vegetables, herbs, spices and medicinal plants, beverages, vegetable oils, cereals, legumes and nuts and other matrices (including cocoa beans and bee products). At the end of the overview, we include two sections to explain the usefulness of the data about phenols provided by capillary electrophoresis and the newest trends.

Antioxidant activity of wines determined by a polarographic assay based on hydrogen peroxide scavenge

Antioxidant (AO) activity of various red and white wines of different origin as well as some individual phenolic compounds present in wine has been assessed using a polarographic assay. Direct current polarography has been used to survey hydrogen peroxide scavenge (HPS) upon gradual addition of tested samples. Results expressed as reciprocal value of wine volume required for 50% decrease of anodic limiting current of hydrogen peroxide have been validated through correlation with Folin-Ciocalteau and DPPH assays. All wines exhibit HPS activity analogous with total phenolic content and DPPH scavenge. Reliability and accuracy, low cost, and rapid and direct experimental procedure open a wide area for application of this assay, making it a good alternative to standard, widely accepted AO assays.

Application of artificial neural networks in the prediction of product distribution in electrophoretically mediated microanalysis

The successful application of artificial neural networks toward the prediction of product distribution in electrophoretically mediated microanalysis is presented. To illustrate this concept, we examined the factors and levels required for optimization of reaction conditions for the conversion of nicotinamide adenine dinucleotide to nicotinamide adenine dinucleotide, reduced form by glucose-6-phosphate dehydrogenase in the conversion of glucose-6-phosphate to 6-phosphogluconate. A full factorial experimental design examining the factors voltage, enzyme concentration, and mixing time of reaction was utilized as input-output data sources for suitable artificial neural networks training for prediction purposes. This approach proved successful in predicting optimal values in a reduced number of experiments. Model validation addressing the extent of reaction and product ratios were subsequently determined experimentally in replicate analyses, with results shown to be in good agreement (<10% discrepancy difference) with predicted data.

Identification of herb Acanthopanax senticosus (Rupr. Et Maxim.) harms by capillary electrophoresis with electrochemical detection

In this paper, a rapid, high efficient, sensitive and inexpensive approach based on a combination of simple ultrasonic extract and capillary electrophoresis (CE) separation with electrochemical detection (ED), is described to identify herbs by comparing their CE-ED profiles (namely, CE-ED electropherograms). The proposed method takes advantage of ultra-small sample volume, low consumption of organic solvent, simple sample pretreatment and easy cleanup procedure. It was applied to analyze the CE-ED profiles of stems of herb Acanthopanax senticosus (Rupr. Et Maxim.) Harms from different sources and different parts (roots, rhizomes, stems and leaves) of this herb. By comparing peak number, peak height and peak height ratio, we found that the CE-ED profiles showed big differences for the herbs from the different sources and the different parts of this herb. In addition, the distribution of bioactive compounds (isofraxidin, rutin and chlorogenic acid) in the different parts of this herb and their content variations affected by the source were studied with the CE-ED method. Based on their own unique CE-ED profiles, these herbs from the different sources and the different parts of this herb could be easily distinguished. Therefore, the proposed approach could be used as a rapid, high efficient and sensitive method for the identification of herbal medicines.

Supervised pattern recognition in food analysis

Data analysis has become a fundamental task in analytical chemistry due to the great quantity of analytical information provided by modern analytical instruments. Supervised pattern recognition aims to establish a classification model based on experimental data in order to assign unknown samples to a previously defined sample class based on its pattern of measured features. The basis of the supervised pattern recognition techniques mostly used in food analysis are reviewed, making special emphasis on the practical requirements of the measured data and discussing common misconceptions and errors that might arise. Applications of supervised pattern recognition in the field of food chemistry appearing in bibliography in the last two years are also reviewed.

Analysis ofSalvia officinalis plant extracts by capillary electrophoresis

Salvia officinalis (commonly called Sage) and similar plants contain many compounds of pharmaceutical interest and are used as a tea or in various pharmaceutical products. In this work, the use of CE for analysis of aqueous or ethanolic extracts from various Salvia plants has been studied. Especially, several buffers like borate, phosphate, acetate, etc., were examined under different concentrations, pH, separation voltage, injection time, and other parameters to find the optimal separation conditions. The optimization was also performed using experimental design and artificial neural networks. The optimal conditions were: separation voltage +20 kV, 40 mM buffer borate, pH 9.2, injection time 5 s, and UV detection at 280 nm. A new CE method has been developed, validated, and applied to analyze samples of S. officinalis from various countries.

Analysis of nephroloxic and carcinogenic aristolochic acids in Aristolochia plants by capillary electrophoresis with electrochemical detection at a carbon fiber microdisk electrode

Aristolochic acids (AAs) are the main bioactive ingredients in the most of Aristolochia plants, which are used to make dietary supplements, slimming pills and Traditional Chinese Medicines (TCMs). Excessive ingestion of AAs can lead to serious nephropathy. Therefore, quantitative analysis and quality control for the plants containing AAs is of great importance. In this paper, capillary electrophoresis (CE) with electrochemical detection (ED) at a 33 microm carbon fiber microdisk electrode (CFE) has been applied to detect AA-I and AA-II in Aristolochia plants. Under the optimum conditions: detection potential at 1.20 V, 2.0 x 10(-2) mol L(-1) phosphate buffer solution (PBS) (pH 10.0), injection time 25 s at a height of 17 cm and separation voltage at 12.5 kV, the AA-I and AA-II were baseline separated within 5 min. Low detection limits for AA-I and AA-II were 4.0 x 10(-8) mol L(-1) and 1.0 x 10(-7) mol L(-1), respectively. Wide linear ranges were from 4.0 x 10(-8) mol L(-1) to 1.9 x 10(-5) mol L(-1) and 1.0 x 10(-7) mol L(-1) to 5.0 x 10(-5) mol L(-1) for AA-I and AA-II, respectively. The proposed method has been successfully applied to analyze AAs contents in plant extracts. The results indicated that the contents of AAs in each part of Aristolochia debilis Sieb. Et Zucc. plant were different. Meanwhile, the CE-ED method was utilized for fingerprint analysis of medicine herbs. Six herbs (Radix aristolochiae, Fructus aristolochiae, Herba aristolochiae, Caulis aristolochiae manshuriensis, Caulis clematidis armandii, Caulis akebiae) were well distinguished by comparing their electropherograms obtained by CE-ED method.