Wine Differentiation According to Color Using Conventional Parameters and Volatile Components

Huerta, Mauricio; Salinas, M. Rosario; Masoud, T.; Alonso, Gonzalo L.

doi:10.1006/jfca.1998.0601

Cited by 9 publications

(9 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Due to this complexity, several chemometric techniques are usually applied to data treatment like principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), hierarchical cluster analysis (HCA), canonical analysis (CA), discriminant analysis (DA), principal component regression (PCR) and partial least square analysis (PLS) (Beebe, Pell, & Seasholtz, 1998;Huerta, Salinas, Masoud, & Alonso, 1998;Massart, Vandeginste, & Deming, 1988). Some of the most important parameters used for the characterization and differentiation of several types of beverages are alcoholic content, ash content, dry extract, pH, fixed acidity, volatile acidity, etc.…”

Section: Introductionmentioning

confidence: 99%

Classification of distilled alcoholic beverages and verification of adulteration by near infrared spectrometry

Pontes

Santos

Araújo

et al. 2006

Food Research International

132

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Classification of distilled alcoholic beverages and verification of adulteration by near infrared spectrometry

Pontes

Santos

Araújo

et al. 2006

Food Research International

132

View full text Add to dashboard Cite

“…The acidity of blackberries changes during growth and ripening and affects the acidity of blackberry juice and must. Consequently, the acidity of must can affect wine because some acids from must transfer to wine and participate in different physico-chemical and biochemical processes, such as wine fl avour formation [Zoecklein et al, 1995;Huerta et al, 1998]. The fi rst indicator of wine acidity is the pH value (Table 1), which ranged from 3.11 (CBW 5) to 3.56 (OBW 13) in the investigated blackberry wines.…”

Section: Physico-chemical Quality Parametersmentioning

confidence: 99%

“…Reducing sugars, glucose and fructose are widely present in foods, especially fruits. Blackberries usually contain 4.9 g sugars per 100 g [Huerta et al, 1998; USDA], and during wine fermentation, both monosaccharides are co-ferment- Legend: values are presented as means of three parallel investigations ± standard deviation (data: mean±SD, n = 3). A 420, A 520, A 620 -A were measured at 420 nm; 520 nm and 620 nm; dA% -% of monomeric anthocyanins.…”

Section: Physico-chemical Quality Parametersmentioning

confidence: 99%

“…In grape wine testing, a high level of acidity refers to excessively tart, sour and sharp wine attributes, while a low total acidity results in a fl at-tasting wine that is more susceptible to infection and spoilage by microorganisms [Zoecklein et al, 1995;Huerta et al, 1998]. The total acidity of the tested samples ( Ash, the inorganic residue remaining after wine burning, was determined gravimetrically in all analysed samples.…”

Section: Physico-chemical Quality Parametersmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of Quercetin Content, Colour and Selected Physico-Chemical Quality Parameters of Croatian Blackberry Wines

Klarić¹,

Klarić²,

Velić³

et al. 2017

Pol. J. Food Nutr. Sci.

View full text Add to dashboard Cite

Blackberry wine, the most widespread Croatian fruit wine, is produced by yeast fermentation of raw blackberry juice or must. Even though the production and intake of blackberry wine in Croatia has been increasing for years, the available data on the overall quality and blackberry wine composition is still scarce. The objective of this work was to evaluate the quercetin content, colour and selected physico-chemical quality parameters of 15 Croatian blackberry wine samples, divided into two groups denominated as CWB and OWB regarding the blackberries' cultivation type (conventional and organic). The quercetin content ranged from 0.81 to 21.67 mg/L (average: 6.16 mg/L, median 3.96 mg/L) and was consistent with some published studies. Compared to CBW group, quercetin content of OBW samples seemed to be more balanced and slightly higher (OBW median: 3.99 mg/L, CWB median: 1.80 mg/L). The presence of cyanidin and pelargonidin (as aglycons) was detected in very low concentrations in four and seven samples, respectively. Determination of the colour revealed that the most important component contributing to colour intensity was yellow (51 %), followed by red (40 %). The chemical quality parameters were in accordance with the available published results on blackberry and grape wines and were as follows: relative density 1.0017-1.0660 g/mL, concentration of reducing sugars 13.5-177.6 g/L, alcoholic strength 9.37-14.78% vol, pH 3.11-3.56, total acidity 6.7-18.1 g/L, ash 1.59-4.11 g/L, alkalinity of ash 1.54-3.79 g/L, total nitrogen 65.50-361.15 mg/L, and total phosphorus 32.03-118.53 mg/L. No signifi cant overall differences were noticed between the conventional and organic group of samples.

show abstract

“…In addition, the differences between the samples may cause very slight spectral differences that are difficult to distinguish. Due to this complexity, several chemometric techniques are usually applied to the data treatment like the principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), hierarchical cluster analysis (HCA), canonical analysis (CA), discriminant analysis (DA), principal component regression (PCR), and partial least square analysis (PLS) (Massart et al 1988;Beebe et al 1998;Huerta et al 1998). While there has been a notable growth for the application of near-infrared spectroscopy (Barboza & Poppi 2003;Pontes et al 2006) and Fourier transform infrared spectroscopy in the mid-infrared range (Palma & Barroso 2002;Lachenmeier et al 2005;Lachenmeier 2007), little research has been carried out using either UV-vis absorption or fluorescence spectroscopy in spirit drink authentication.…”

mentioning

confidence: 99%

Total luminescence spectroscopy for differentiating between brandies and wine distillates

Tóthová¹,

Sádecká²,

Májek³

2009

Czech J. Food Sci.

View full text Add to dashboard Cite

Tóthová J., Sádecká J., Májek P. (2007): Total luminescence spectroscopy for differentiating between brandies and wine distillates. Czech J. Food Sci., 27: 425-432.In this study, the differentiation was investigated between brandy and wine distillate samples by fluorescence spectroscopy in combination with multivariate analysis. The samples corresponding to eight brandies from three producers and sixteen wine distillates from five producers were acquired in the local supermarkets. Total luminescence spectra of diluted and undiluted samples were recorded. In order to extract reliable information from the data sets, two multivariate analysis methods, Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA), were applied separately on the excitation and emission spectra. The best differentiation was achieved using the emission spectra (400-470 nm) recorded at the excitation wavelength of 340 nm, or the excitation spectra (240-380 nm) recorded at the emission wavelength of 450 nm. The similarity map defined by the PC1 and PC2 of the PCA performed on the excitation spectra accounted for 94.9% of the total variance (PC1 90.3%, PC2 4.6%) and allowed a good discrimination between the beverages. Although the PCA similarity map defined by the PC1 (84.2%) and PC2 (13.0%) performed on the emission spectra did not lead to a clear discrimination between the beverages, a general trend pointing out the brandies and wine distillates was observed on the map. HCA performed on the excitation spectra provided a better differentiation between the two classes, without any classification error, while HCA performed on the emission spectra allowed 95.8% correct classification.

show abstract

Wine Differentiation According to Color Using Conventional Parameters and Volatile Components

Cited by 9 publications

References 19 publications

Classification of distilled alcoholic beverages and verification of adulteration by near infrared spectrometry

Classification of distilled alcoholic beverages and verification of adulteration by near infrared spectrometry

Evaluation of Quercetin Content, Colour and Selected Physico-Chemical Quality Parameters of Croatian Blackberry Wines

Total luminescence spectroscopy for differentiating between brandies and wine distillates

Contact Info

Product

Resources

About