ArticleJournal of agricultural and food chemistry2024
Volatile Organic Compound-Based Predictive Modeling of Smoke Taint in Wine.
Article in Journal of agricultural and food chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Molecular Atlas of Key Food Odorants Reveals Mixture-Level Organization and Enables Generative Aroma Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Oak aging mitigates the sensory impact of smoke taint in Cabernet Sauvignon wine.Scientific reports · 2026Article
- Single nucleotide polymorphism information estimates breed and variety composition ratio in food.Current research in food science · 2026Article
- Diversity of volatile phenols and their newly identified precursors during different grape species development.Frontiers in plant science · 2026Article
- Discrepancy Between the Ability of Wine Experts and Consumers in Identifying Grape Smoke Exposure in Different Wine Matrices in California.Journal of food science · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Smoke taint in wine has become a critical issue in the wine industry due to its significant negative impact on wine quality. Data-driven approaches including univariate analysis and predictive modeling are applied to a data set containing concentrations of 20 VOCs in 48 grape samples and 56 corresponding wine samples with a taster-evaluated smoke taint index. The resulting models for predicting the smoke taint index of wines are highly predictive when using as inputs VOC concentrations after log conversion in both grapes and wines (Pearson Correlation Coefficient PCC = 0.82;
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Registered trials
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