scholarly journals Determination of Phenolic Cinnamates in White Wine and Their Effect on Wine Quality

1981 ◽  
Vol 45 (9) ◽  
pp. 2063-2070 ◽  
Author(s):  
Shigemichi Okamura ◽  
Masazumi Watanabe
Keyword(s):  
White Wine ◽  
Wine Quality

scholarly journals Determination of Iron, Copper and Zinc in the Wine by FAAS

2020 ◽  
Vol 4 (5) ◽  
pp. 411-417
Author(s):  
Valon Ylvi Durguti ◽  
Suzana Aliu ◽  
Fisnik Laha ◽  
Fidan Feka
Keyword(s):  
Heavy Metals ◽  
Human Health ◽  
White Wine ◽  
Wine Quality ◽  
Flame Atomic Absorption Spectroscopy ◽  
Analytical Technique ◽  
Eu Directive ◽  
Flame Atomic Absorption ◽  
The Eu

Objectives: The purpose of this paper has been to determine quantitatively the presence of some heavy metals (Fe, Cu and Zn) which are of particular importance for the wine quality and human health. A total of 41 samples have been analyzed during different stages of winemaking. Methods: The determination of heavy metals is done by analytical technique known as Flame Atomic Absorption Spectroscopy (FAAS). The limit set by the EU directive EC 606/2009 and International Office of Vine and Wine (OIV) has been taken as reference values. Results and Discussion: None of the analyzed samples has exceeded the limits set by the EU and OIV, excluding the type of white wine known as Rhine Riesling. In this sample the Cu concentration exceeds several times the permissible values. Findings: It has been observed that heavy metals immediately after the alcoholic fermentation process probably continue to remain even for a while in the upper part until wine sediment forms at the bottom of the tank. A higher concentration of heavy metals was observed in the samples taken from the bottom of the wine tank. Conclusion: The analyzed wines samples do not pose a risk in the future to human health. Doi: 10.28991/esj-2020-01240 Full Text: PDF

scholarly journals Determination of phenolic cinnamates in white wine and their effect on wine quality.

1981 ◽  
Vol 45 (9) ◽  
pp. 2063-2070 ◽  
Author(s):  
Shigemichi OKAMURA ◽  
Masazumi WATANABE
Keyword(s):  
White Wine ◽  
Wine Quality

scholarly journals Fast and Reliable Multiresidue Analysis of Aromas in Wine by Means of Gas Chromatography Coupled with Triple Quadrupole Mass Spectrometry

Analytica ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 38-49
Author(s):  
Ettore Guerriero ◽  
Massimo Iorizzo ◽  
Marina Cerasa ◽  
Ivan Notardonato ◽  
Bruno Testa ◽  
...  
Keyword(s):  
Direct Injection ◽  
Headspace Analysis ◽  
White Wine ◽  
Quadrupole Mass ◽  
Multiresidue Analysis ◽  
Liquid Liquid Extraction ◽  
Volatile Organic ◽  
Steel Tank ◽  
First Time

The paper would like to show a direct injection into GC-MS/QqQ for the determination of secondary aromas in white wine samples fermented in two different ways. The procedure has been compared with more traditional methods used in this field, i.e., headspace analysis and liquid–liquid extraction. The application of such direct injection, for the first time in the literature, allows us to analyze Volatile Organic Compounds (VOCs) in the range 0.1–100 µg mL−1, with Limits of Detection (LODs) and Limits of Quantification (LOQs) between 0.01–0.05 µg mL−1 and 0.03–0.09 µg mL−1, respectively, intraday and interday below 5.6% and 8.5%, respectively, and recoveries above 92% at two different fortification levels. The procedure has been applied to real wine samples: it evidences how the fermentation in wood (cherry) barrel yields higher VOC levels than ones in wine fermented in steel tank, causing production of different secondary aromas and different relative flavors.

Determination of Total Carbohydrates in Wine and Wine-Like Beverages by HPLC with a Refractive Index Detector: First Action 2013.12

2014 ◽  
Vol 97 (2) ◽  
pp. 498-505 ◽  
Author(s):  
Steve Kupina ◽  
Mark Roman ◽  
D Anderson ◽  
S Bhandari ◽  
M S Cardozo ◽  
...  
Keyword(s):  
Refractive Index ◽  
Reference Material ◽  
Organic Acids ◽  
Red Wine ◽  
Collaborative Study ◽  
Ion Exchange Resin ◽  
White Wine ◽  
Negative Control ◽  
Total Carbohydrates

Abstract An international collaborative study was conducted of an HPLC-refractive index (RI) detector method for the determination of the combined amounts of sugars, glycerol, organic acids, and phenolic compounds in wines and wine-like beverages. Nine collaboratinglaboratories representing major winery, contract laboratories, and government laboratories tested eight different materials as blind duplicates using the proposed method. Sample materials included red and white wines, port, wine cooler, and nonalcoholic wine. One material was a negative control, and one material was a reference material. Samples were either treated with an ion-exchange resin to remove interferingorganic acids prior to analysis or left untreated toinclude organic acids and phenolics. Red wine samples were treated with polyvinylpolypyrrolidone to remove potential interferences from phenolics prior to analysis. The HPLC analyses were performed on a Bio-Rad Fast Acid Analysis Column using RI detection. Reproducibility (RSDR) for untreated samples(sugars + phenolics + organic acids) ranged from 6.6% for Titrivin AA4 reference material to 11.0% for dry red wine. RSDR for treated samples (sugars only) ranged from 6.8% for white zinfandel to 18.9% for dry white wine. RSDR for treatedsamples (sugars only) + glycerol ranged from 6.4% for white zinfandel to 19.8% for dry red wine. Based on these results, the method was adopted as Official First Action status for determination of total carbohydrates in wine and wine-like beverages.

Monitoring of yeast population isolated during spontaneous fermentation of Moravian wine

2012 ◽  
Vol 66 (9) ◽  
Author(s):  
Hana Šuranská ◽  
Dana Vránová ◽  
Jiřina Omelková ◽  
Renáta Vadkertiová
Keyword(s):  
Fermentation Process ◽  
Rhodotorula Glutinis ◽  
Its Region ◽  
White Wine ◽  
Rapid Identification ◽  
Wine Quality ◽  
Spontaneous Fermentation ◽  
Grape Berries ◽  
Yeast Population ◽  
Sporidiobolus Salmonicolor

AbstractIn enology, yeasts play an important role in the characteristics of the final product. They are predominant in the biochemical interaction with components of must. Rapid identification of the yeast population is necessary for fermentation process monitoring and for obtaining a good quality wine. The main goal of this study was the isolation and characterisation of the yeast microbial community naturally present on grape berries, leaves and occurring during the spontaneous fermentation process of the white wine Veltlin green from the South Moravian region, Czech Republic. The results, based on PCR-RFLP of the 5.8S-ITS region of rDNA, PCR-fingerprinting using microsatellite oligonucleotide primers (GAG)5, (GTG)5, (GAC)5, and M13 primer, showed great diversity of the yeast population. Including grape berries and fermented must, the following yeast species were identified: Hanseniaspora uvarum, Aureobasidium pullulans, Metschnikowia pulcherrima, Torulaspora delbrueckii, a number of Pichia species such as P. fermentans, P. membranifaciens, P. kluyveri, also Sporidiobolus salmonicolor, Rhodosporidium toruloides, Rhodotorula mucilaginosa, Rhodotorula glutinis as well as Saccharomyces cerevisiae and Saccharomyces bayanus. Monitoring of the yeast strains during the wine fermentation process of traditional Moravian wine can contribute to the improvement of wine quality.

scholarly journals Determination of titratable acidity in white wine

2007 ◽  
Vol 52 (2) ◽  
pp. 169-184 ◽  
Author(s):  
Milos Rajkovic ◽  
Ivana Novakovic ◽  
Aleksandar Petrovic
Keyword(s):  
Tartaric Acid ◽  
Potentiometric Titration ◽  
Ph Value ◽  
Titratable Acidity ◽  
White Wine ◽  
Selective Electrode ◽  
Alcohol Fermentation ◽  
Standard Methods ◽  
Illegal Acts

The amount of titration acid in must is in the largest number of cases with in the range 5.0-8.0 g/dm3. Wines, as a rule, contain less acids than must, and according to Regulations, titratable acidity is in the range of 4.0-8.0 g/dm3 expressed in tartaric acid, because a part of tartaric acid is deposited in the form of salts (tartar or argol) during alcohol fermentation. For wines that contain less than 4 g/dm3 of titratable acids there arises a suspicion about their origin, that is, that during the preparation some illegal acts were done. Because of that, the aim of this paper is to determine titratable acidity in white wine, using standard methods of determination, which are compared with the results received by potentiometric titration using ion-selective electrode. According to the received results it can be seen that wine titration with indicator gives sufficient reliable values of wine titration acidity. However, as potentiometric titration at pH value 7.00 is more reliable and objective method, the values of titratable acids content in wine, expressed through tartaric acid, are given according to this result. The analysis of differential potentiometric curves shows that these curves can give us an answer to the question of the presence of a larger amount of other nonorganic substances, which have already existed in wine. However, none of the used methods gives absolutely reliable answer what substances are present in analysed samples.

scholarly journals Gelatine, casein and potassium caseinate as distinct wine fining agents: different effects on colour, phenolic compounds and sensory characteristics

OENO One ◽  
2007 ◽  
Vol 41 (4) ◽  
pp. 203 ◽  
Author(s):  
Asençao Braga ◽  
Fernanda Cosme ◽  
Jorge Manuel Ricardo-da-Silva ◽  
Olga Laureano
Keyword(s):  
Phenolic Compounds ◽  
Charge Density ◽  
Surface Charge ◽  
Surface Charge Density ◽  
White Wine ◽  
Sensory Characteristics ◽  
Wine Quality ◽  
Physico Chemical ◽  
Fining Agents ◽  
Monomeric Anthocyanins

<p style="text-align: justify;"><strong>Aims</strong>: Describe and compare some characteristics, such as molecular weight (MW) distribution and surface charge density of commercial protein fining agents and to enhance the understanding of their effect on wine chemical and sensory characteristics.</p><p style="text-align: justify;"><strong>Methods and results</strong>: Protein (casein, potassium caseinate and gelatine) MW distribution was characterised by electrophoresis. These proteins were added to a red and a white wine, in order to evaluate its effect on colour, phenolic compounds and sensory attributes.</p><p style="text-align: justify;"><strong>Conclusion</strong>: A band at 30.0 kDa characterised casein and potassium caseinate. Gelatines showed polydispersion on the MW distribution, gelatine GSQ on the higher MW (&gt; 43.0 kDa) and gelatine GL on the lower MW (&lt; 43.0 kDa). Despite the fact that casein and potassium caseinate had similar MW distribution, casein decreased essentially the monomeric ((+) - catechin and (-) - epicatechin) while the potassium caseinate showed a lower influence on these compounds. Also, among the two gelatines used, a different behaviour was observed. The gelatine characterised by a polydispersion below 43.0 kDa depleted more the polymeric tannin fractions than the gelatine characterised by a polydispersion above 43.0 kDa. That gelatine has also decreased colour intensity and coloured anthocyanins of red wine but the hue remains unchanged. Addition of fining agents did not affect greatly the concentration of monomeric anthocyanins. Sensory analysis showed that wines fined with the different proteins presented distinct characteristics.</p><p style="text-align: justify;"><strong>Significance and impact of study</strong>: The knowledge of the physico-chemical characteristics, such as MW distribution and surface charge density, is important for wine fining optimisation and consequently for the wine quality.</p>

Determination of Color in White Wine and White Grape Juice Using the White Wine Colorimeter

1977 ◽  
Vol 60 (3) ◽  
pp. 739-740
Author(s):  
Herb L Wildenradt ◽  
Paul A Stafford
Keyword(s):  
Grape Juice ◽  
White Wine ◽  
Color Measurement ◽  
White Wines ◽  
Reproducible Method ◽  
Grape Juices

Abstract Further experience with the white wine colorimeter has demonstrated that this instrument provides a simple and reproducible method of color measurement for both finished and unfinished white wines and white grape juices. In view of the proven accuracy and utility of the white wine colorimeter, the method specifying this instrument, 11.B01–11.B02, has been adopted as official final action.

scholarly journals Determination of Ochratoxin A in Wine and Beer by Immunoaffinity Column Cleanup and Liquid Chromatographic Analysis with Fluorometric Detection: Collaborative Study

2001 ◽  
Vol 84 (6) ◽  
pp. 1818-1827 ◽  
Author(s):  
Angelo Visconti ◽  
Michelangelo Pascale ◽  
Gianluca Centonze ◽  
E Anklam ◽  
A M Betbeder ◽  
...  
Keyword(s):  
Ochratoxin A ◽  
Red Wine ◽  
Collaborative Study ◽  
White Wine ◽  
Fluorometric Detection ◽  
Immunoaffinity Column ◽  
Relative Standard ◽  
Standard Deviations ◽  
Liquid Chromatographic

Abstract The accuracy, repeatability, and reproducibility characteristics of a liquid chromatographic method for the determination of ochratoxin A (OTA) in white wine, red wine, and beer were established in a collaborative study involving 18 laboratories in 10 countries. Blind duplicates of blank, spiked, and naturally contaminated materials at levels ranging from ≤0.01 to 3.00 ng/mL were analyzed. Wine and beer samples were diluted with a solution containing polyethylene glycol and sodium hydrogen carbonate, and the diluted samples were filtered and cleaned up on an immunoaffinity column. OTA was eluted with methanol and quantified by reversed-phase liquid chromatography with fluorometric detection. Average recoveries from white wine, red wine, and beer ranged from 88.2 to 105.4% (at spiking levels ranging from 0.1 to 2.0 ng/mL), from 84.3 to 93.1% (at spiking levels ranging from 0.2 to 3.0 ng/mL), and from 87.0 to 95.0% (at spiking levels ranging from 0.2 to 1.5 ng/mL), respectively. Relative standard deviations for within-laboratory repeatability (RSDr) ranged from 6.6 to 10.8% for white wine, from 6.5 to 10.8% for red wine, and from 4.7 to 16.5% for beer. Relative standard deviations for between-laboratories reproducibility (RSDR) ranged from 13.1 to 15.9% for white wine, from 11.9 to 13.6% for red wine, and from 15.2 to 26.1% for beer. HORRAT values were ≤0.4 for the 3 matrixes.

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