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Enregistrement W998577182

The colour of red wine.

2007· dissertation· en· W998577182 sur OpenAlexfundno aff
Maria Josephine Birse

Notice bibliographique

RevueAdelaide Research & Scholarship (AR&S) (University of Adelaide) · 2007
Typedissertation
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueFermentation and Sensory Analysis
Établissements canadiensnon disponible
Organismes subventionnairesInstitut National Du CancerAlberta Water Research Institute
Mots-clésDeclarationWineTable (database)Table of contentsLibrary scienceHistoryInformation retrievalClassicsComputer scienceArtWorld Wide WebData miningVisual arts
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The behaviour of pigments in red wine, namely anthocyanins and anthocyaninderived pigments, was investigated at natural wine pH, at low pH and after addition of SO2, namely SO2 bleaching. An examination of current literature demonstrated absences in wine pigment research. Firstly, few researchers have published the colour properties of a particular wine pigment at different pH values and post-SO2 bleaching. This was demonstrated using the CIELab colours of two individual anthocyanin-derived wine pigments (4-vinylcatechol and 4-vinylsyringol adducts to malvidin 3-glucoside), and an anthocyanin, malvidin 3-glucoside. The colours of the anthocyanin-derived pigments and their resistance to pH change and SO2 bleaching were compared to malvidin 3-glucoside which was affected by media.
\nGenerally, in the literature, wine pigments are characterized as individual components. But many pigments contribute to wine colour. So, two novel methods were created and demonstrated using red wines: Shiraz wines from four regions in
\nAustralia, and Cabernet Sauvignon wines made using two different strains, Saccharomyces cerevisiae (SC) or Saccharomyces bayanus (SB). The first method can be used to determine the CIELab colour of chromatographically separated wine pigments and allows their colours to be re-created, regardless of their identity. Thus objective measurement of pigment colour at its natural concentration in wine is now possible.
\nAn additional method, the “post-column adjustment method” to pH-adjust and SO2 bleach HPLC-separated wine pigments was created. The concentration and colour of HPLC-separated wine pigments at low pH, at wine pH and post-SO2 bleaching can be measured. The method has highlighted the importance of the pH value when quantifying a wine pigment. For example, from low pH to wine pH, the apparent anthocyanin and pigmented polymer concentration was reduced, but the Vitisin A concentration was unchanged. SO2 bleaching resulted in negligible anthocyanin concentration and a further reduction in pigmented polymer concentration, with Vitisin A unaffected. Relative quantities of wine pigments in both SC and SB Cabernet Sauvignon wines were not affected by pH change or SO2 bleaching.
\nAlso, using the Shiraz wines and Cabernet Sauvignon red wines, existing and improved colour measurement techniques were discussed. For the Australian Shiraz wines, grape origin was found to influence red wine colour, CIELab values provided enhanced colour measurements, and high wine colour (at natural wine pH) cannot be attributed to individual monomeric anthocyanins (measured by HPLC analysis at low pH). Vitisin A was not responsible for differences in wine colour. SO2-stable wine colour was related to regional differences. The percentage of SO2 non-bleachable pigments was independent of wine region. Chemical index (ii) values indicated that the colour at 520 nm was attributable to pH-dependent wine pigments. Vitisin A and
\npigmented polymer concentrations correlated well with SO2-stable wine colour. Pigmented polymer concentration may be the driving force behind wine colour density. Copigmentation was of no importance in the young red wine samples studied.
\nWith the Cabernet Sauvignon red wines, the yeast strains used for fermentation affected wine colour and SO2-stable wine colour. The change in wine colour density was not related to change in total red pigment colour or anthocyanin concentration.
\nPigmented polymer concentration, SO2-stable wine colour and the percentage of SO2 non-bleachable pigments were consistently higher in the SB wines.
\nThe pH value was important when determining the colour of a wine or pigment. At low pH, the SC wines were more coloured than the SB wines. However, at real wine pH, the converse was true. For both wines, at low pH, the anthocyanin concentration was greater than the pigmented polymer concentration, indicating the importance of anthocyanins to wine colour only at low pH. But, at wine pH, the apparent anthocyanin concentration was much lower in both wines (for example, malvidin 3- glucoside provided more colour at low pH than at wine pH) than the apparent pigmented polymer concentration. Therefore, at wine pH, anthocyanins were less important to wine colour than pigmented polymers.
\nThe concentrations of Vitisin A were similar in all three media, but colour losses were observed at wine pH and post-SO2 bleaching. SB Vitisin A was more coloured. At low pH and at wine pH, Vitisin A was more coloured than malvidin 3-glucoside in both wines, even though the apparent Vitisin A concentration was lower. Differences in the colours of the SC and SB pigmented polymers peaks were observed at low pH, at wine pH and following SO2 bleaching. The SB pigmented polymers were darker and more colourful, exhibited more colour absorbance and a slight bathochromic shift of lmax value. From low pH to wine pH and following SO2 bleaching, pigmented polymers become lighter, whilst retaining orange-red hues.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,779
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,002
Études des sciences et des technologies0,0020,000
Communication savante0,0000,000
Science ouverte0,0020,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,083
Tête enseignante GPT0,347
Écart entre enseignants0,264 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations21
Publié2007
Routes d'admission1
Résumé présentoui

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