Sensory and chemical profiling of Cypriot wines made from indigenous grape varieties Xynisteri, Maratheftiko and Giannoudhi and acceptability to Australian consumers
Notice bibliographique
Résumé
Aim: The aims of this study were to (1) generate sensory and chemical profiles of commercial Cypriot wines made from the white grape Xynisteri and the red grapes Maratheftiko and Giannoudhi and (2) assess the Australian consumers’ response to these wines.Methods and Results: A Rate-All-That-Apply (RATA) method was used for sensory profiling of the wines (n=56 panellists on Xynisteri and n=60 on Maratheftiko and Giannoudhi) and to guide chemical analysis of flavour compounds. Chemical analysis involved quantitative analysis of aroma compounds by gas chromatography mass spectrometry (GC-MS) and non-targeted profiling of phenolic compounds (non-volatile secondary metabolites) using liquid chromatography mass spectrometry (LC-MS). Australian wine consumer’s hedonic responses towards wines made from Cypriot grape varieties were also investigated. Consumers completed a questionnaire exploring their demographics, wine consumption habits, environmental/sustainability opinions and neophobic tendencies prior to the tasting. The first tasting (n consisted of six commercial Xynisteri, one Australian Pinot Gris and one Australian unwooded Chardonnay wines. The second (n=114) consisted of three Maratheftiko, one Giannoudhi and one Australian Shiraz wines.Conclusions: Principal Component Analysis (PCA) of the RATA study identified the following sensory characteristics for Xynisteri wine: stone fruit, dried fruit, citrus, herbaceous, grassy, apple/pear, confectionary, vanilla, creamy, buttery, wood, and toasty. Maratheftiko wines were described as woody, dried fruit, chocolate, herbaceous, confectionary, jammy, sweet and full bodied. Giannoudhi wine was described as woody, dried fruit, chocolate and full bodied. Chemical analysis identified 15 phenolic compounds in the white wine samples and 17 in the red wine samples, as well as 21 volatile/aroma compounds in the white wine samples and 26 in the red wine samples. These chemical compounds were then correlated with sensory data from the RATA and consumer hedonic responses using Agglomerative Hierarchical Clustering (AHC) and PCA to determine consumer liking drivers for the wines. Three clusters of consumers were identified for the white and red wines. The overall consumer means for liking indicated that Cypriot wines were liked similarly to Australian wines.Significance and impact of the study: Australia’s changing climate is placing great pressure on the resources for sustainable viticulture. Many vineyards and wineries base their businesses on European grape varieties traditionally grown in regions with abundant water resources. It is therefore necessary for the Australian wine industry to investigate grape varieties that are indigenous to hot climates similar to Australia. The eastern Mediterranean island of Cyprus is one such place with indigenous grape varieties that grow well in a hot climate without irrigation. These popular Cypriot wines have the potential to be popular with Australian consumers, thus offering new grape varieties to the Australian market that are better suited to the changing climate.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».