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Article details
Title
Models based on ultraviolet spectroscopy, polyphenols, oligosaccharides and polysaccharides for prediction of wine astringency
Published in
Food Chemistry, May 2015
DOI 10.1016/j.foodchem.2015.05.062
Pubmed ID
Authors
Abstract

Astringency elicited by tannins is usually assessed by tasting. Alternative methods involving tannin precipitation have been proposed, but they remain time-consuming. Our goal was to propose a faster method and investigate the links between wine composition and astringency. Red wines covering a wide range of astringency intensities, assessed by sensory analysis, were selected. Prediction models based on multiple linear regression (MLR) were built using UV spectrophotometry (190-400nm) and chemical analysis (enological analysis, polyphenols, oligosaccharides and polysaccharides). Astringency intensity was strongly correlated (R(2)=0.825) with tannin precipitation by bovine serum albumin (BSA). Wine absorbances at 230nm (A230) proved more suitable for astringency prediction (R(2)=0.705) than A280 (R(2)=0.56) or tannin concentration estimated by phloroglucinolysis (R(2)=0.59). Three variable models built with A230, oligosaccharides and polysaccharides presented high R(2) and low errors of cross-validation. These models confirmed that polysaccharides decrease astringency perception and indicated a positive relationship between oligosaccharides and astringency.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
South Africa 1 <1%
United States 1 <1%
Unknown 106 98%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 24 22%
Student > Master 16 15%
Student > Bachelor 10 9%
Student > Ph. D. Student 9 8%
Student > Doctoral Student 6 6%
Other 12 11%
Unknown 31 29%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 43 40%
Chemistry 13 12%
Biochemistry, Genetics and Molecular Biology 9 8%
Engineering 3 3%
Environmental Science 2 2%
Other 3 3%
Unknown 35 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 June 2015.
All research outputs
#27,205,565
of 32,950,213 outputs
Outputs from Food Chemistry
#10,749
of 15,445 outputs
Outputs of similar age
#228,482
of 298,735 outputs
Outputs of similar age from Food Chemistry
#135
of 183 outputs
Altmetric has tracked 32,950,213 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15,445 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.8. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 298,735 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 183 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.