Models based on ultraviolet spectroscopy, polyphenols, oligosaccharides and polysaccharides for prediction of wine astringency

Boulet, Jean Claude; Trarieux, Corinne; Souquet, Jean‐Marc; Ducasse, Maris-Agnès; Caillé, Soline; Samson, Alain; Williams, Pascale; Doco, Thierry; Cheynier, Véronique

doi:10.1016/j.foodchem.2015.05.062

Cited by 73 publications

(53 citation statements)

References 23 publications

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“…The variables on the right of the plane (A280, TP, TT, 3-methyl-1-butanol and acetic acid) were more associated with the separation of the wines from TO and CI. The A230 and A280 measurements have been commonly used for a rapid determination of the total phenolic content in wines (Kennedy et al, 2006;Boulet et al, 2016) due to their high correlation with these wine compounds. Nevertheless, the relative contribution of A230 with tannins, other polyphenols, or other wine compounds contents, are not clear yet (Boulet et al, 2016).…”

Section: Resultsmentioning

confidence: 99%

Stepwise linear discriminant analysis to differentiate Spanish red wines by their Protected Designation of Origin or category using physico-chemical parameters

et al. 2020

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a b s t r a c tAim: The aim of this work was to determine the physico-chemical variables that differentiating red wines from the "Castilla y León" Spanish region by their Protected Designation of Origin (PDO) and wine category ("young", "oak", "crianza", or "reserve"). Methods and results: A total of 135 commercial red wines from four Spanish PDOs in the region of Castilla and León were analysed. Forty physico-chemical parameters, related to classical enological parameters, phenolic and polysacharidic composition, and content of higher alcohols were evaluated. Differences in physico-chemical composition were found in red wines from different PDOs and different categories. Stepwise linear discriminant analysis (SLDA) was applied to find a linear combination of the physico-chemical variables that separate and classify the red wines according to the PDO or category. One SLDA model selected 15 physico-chemical variables that allowed for good discrimination and classification of the wines from different PDOs. The SLDA model selected seven variables for wine category differentiation, but only allowed for good discrimination between young wines and aged wines ("crianza" and "reserve"). Conclusions:The variables that contributed most to the separation of Tempranillo red wines were total polyphenols, total tannins, and absorbance values at 230 nm and 280 nm. The polysaccharides with an average molecular weight of 10 kDa, flavanols, stilbenes and 2-methyl-1-butanol were those most associated with the differentiation of the wines elaborated with the Mencía grape variety. The percentage of polymeric anthocyanins and absorbance at 230 nm could be proposed as good indicators for aged wines, and total tannins for young wines. Significance and impact of the study: This study provides improved knowledge of the physico-chemical variables that could be used as markers of the origin of wines and/or the grape variety (Tempranillo and Mencía) and that allow differentiating young wines from those aged for a long time. k e y w o r d s higher alcohols, organic acids, phenolic compounds, polysaccharides, Protected Designation of Origin, red wine categories, stepwise linear discriminant analysis

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Section: Resultsmentioning

confidence: 99%

Stepwise linear discriminant analysis to differentiate Spanish red wines by their Protected Designation of Origin or category using physico-chemical parameters

et al. 2020

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“…The effect of the fining treatment on wine astringency was attempted by means of chemical and sensory methods in order to investigate if the significant reduction in the content of phenolic compounds effectively influenced astringency. The results obtained from the BSA precipitation index, as described by Boulet et al [32], and from tasting sessions by a trained panel on astringency are shown in Table 3. Astringency determinations gave different results depending on the analytical method: the BSA index highlighted significant differences whereas the sensory-perceived intensity by the trained panel had not shown relevant differences in terms of astringency among fining treatments.…”

Section: Astringency and Visual Color Assessmentmentioning

confidence: 99%

“…The removal of flavanols, oligomeric or polymeric, is not always directly related to a reduction of astringency, either sensory perceived or chemically assessed. This could be due to the complexity of astringency sensation, which can be mainly triggered by polymeric flavanols of different subunit composition and modified by wine features such as alcohol content, acidity, and pH [32,33]. It is well known that the perceived astringency is increased at lower pH values.…”

Section: Astringency and Visual Color Assessmentmentioning

confidence: 99%

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Phenolic Composition Influences the Effectiveness of Fining Agents in Vegan-Friendly Red Wine Production

et al. 2019

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Plant proteins have been proposed as an alternative to animal-origin proteins in the wine industry because they are allergen-free and vegan-friendly. The aim of this study was to evaluate the effectiveness of plant proteins as fining agents on red wines with different phenolic composition. Two formulations for commercially available vegetal proteins (potato and pea origin) were assessed at two doses to modulate the fining treatment to the wine phenolic profile. The results evidenced that fining agents derived from plants have different levels of effectiveness on the removal of phenolic compounds depending on the origin, the formulation used, dose applied, and also wine characteristics. On Nebbiolo wine, the study was particularly significant due to its phenolic composition. One pea-based fining agent had an effect comparable to gelatin (animal origin) on the removal of polymeric flavanols with a minor loss of anthocyanins and therefore better preserving the wine color in terms of intensity and hue. For Primitivo, Montepulciano, and Syrah wines, even though there was a formulation-dependent effect, vegetal proteins gave more balanced reductions in terms of target phenolic compounds contributing to astringency and color perception.Molecules 2020, 25, 120 2 of 20 isolated from cereals, legumes, potatoes [6,7], seaweeds, grape seed extracts [8,9], and yeasts [10,11]. Other vegetal non-proteinaceous products, such as polysaccharide-based agents isolated from cell wall material of fresh apples and grapes or their respective pomaces, have shown great potential for wine fining purposes [12][13][14][15].Focusing on protein-based fining agents, they can have a different affinity to different types of phenolic compounds. Proteins interact with wine phenolic compounds initially through hydrogen bonding and hydrophobic interactions, forming soluble complexes. In fact, gelatin is a highly efficient fining agent because of its potential hydrogen binding sites [3]. Subsequently, phenolic compounds are removed by precipitation through self-association of the complexes formed [16] or formation of insoluble protein aggregates (cross-linkages between proteins) incorporating the target species [17]. This precipitation induces reduced astringency and depends on the protein to tannin ratio as well as on the amino acid composition, tertiary structure, hydrophobicity, and molecular mass of proteins [2,18]. It is well-known that proline-rich proteins have a strong affinity to phenolic compounds and therefore they are of great interest for wine fining [19]. Concretely, aromatic ring structures of phenolic compounds have hydrophobic properties and the presence of galloylated units enhances the hydrophobic interactions with proline-rich proteins [20].Among allergen-free vegetal proteins isolated from cereals, corn zeins are a heterogeneous protein mixture made of polypeptides differing in molecular mass, aggregation state, and isoelectric point. The effectiveness of zein as a fining agent could be due to their relative hydrophobicity, which ...

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“…Bitterness and astringency can differ in wines and ciders with the same reported total polyphenol content due to variations in sensory impact among polyphenols (Brossaud, Cheynier, & Noble, ; Lea & Arnold, ). Several methods for polyphenol quantification have been used as predictors of bitterness and/or astringency; however, identifying the most effective method for this purpose remains a topic of current research (Boulet et al., ).…”

Section: Introductionmentioning

confidence: 99%

Comparison of Common Analytical Methods for the Quantification of Total Polyphenols and Flavanols in Fruit Juices and Ciders

Kim

Neilson

et al. 2019

Journal of Food Science

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Multiple analytical methods are used for quantification of total polyphenols and total flavanols in fruit juices and beverages. Four methods were evaluated in this study: Folin‐Ciocalteu (F‐C), Lowenthal permanganate (L‐P), 4‐dimethylaminocinnamaldehyde (DMAC), and the bovine serum albumin (BSA) precipitation method. Method validation parameters, including working range, limit of detection, limit of quantitation, precision (repeatability), accuracy, and specificity, were assessed and compared. The F‐C method was not specific to polyphenols, and the L‐P method had the widest working range but lacked accuracy. The DMAC method was the most specific to flavanols, and the BSA method was not suitable for quantification of smaller flavanols, such as catechin and epicatechin. Quantitative performance was evaluated using commercial fruit juice samples (n = 14), apple juice samples of different cultivars (n = 22), and commercial ciders (n = 17). In general, the L‐P titration method and DMAC method resulted in higher quantitative values than the F‐C method and BSA precipitation method, respectively. However, ratios of results obtained by the L‐P and F‐C method ranged from 1 to 28, and ratios of results obtained by the DMAC and BSA precipitation method ranged from <1 to 280. This tremendous variation is likely due to variation in polyphenol composition and sample matrix. This information provides perspective for comparison of results obtained through these different methods, and a basis for choosing the most appropriate analytical method for quantification of polyphenols to address a specific research question when working with commercial fruit juice, apple juice from different apple cultivars, and commercial ciders. Practical Application This study compared results obtained when four common polyphenol quantification methods were applied to a diverse selection of fruit juices and beverages with distinct polyphenol composition and sample matrix. The matrix and polyphenol composition of the samples significantly influenced the results. Our findings can help manufacturers of fruit‐based products choose the most appropriate analytical method for polyphenol quantification as part of a quality assurance program or to convey information on dietary polyphenol content to consumers. An assessment of analytical method validation parameters is provided for each of the four methods, which will help users of these methods to understand their limitations.

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Models based on ultraviolet spectroscopy, polyphenols, oligosaccharides and polysaccharides for prediction of wine astringency

Cited by 73 publications

References 23 publications

Stepwise linear discriminant analysis to differentiate Spanish red wines by their Protected Designation of Origin or category using physico-chemical parameters

Stepwise linear discriminant analysis to differentiate Spanish red wines by their Protected Designation of Origin or category using physico-chemical parameters

Phenolic Composition Influences the Effectiveness of Fining Agents in Vegan-Friendly Red Wine Production

Comparison of Common Analytical Methods for the Quantification of Total Polyphenols and Flavanols in Fruit Juices and Ciders

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