Iowa wine: Consumer perception, typical composition, and evaluation of strategies to remediate low red wine tannin
Bibliographic record
Abstract
The Iowa grape and wine industry has a rich history which began in the 19th century; however, a major decline saw the industry all but disappear by the mid 20th century. With the breeding and release of interspecific cold-hardy hybrid cultivars, the Iowa grape and wine industry was revitalized near the turn of the 21st century. Overall wine quality has improved over the last 20 years, however there are still grape-growing and winemaking challenges that need solutions. There are few to no reports for interspecific cold-hardy cultivars concerning wine chemical parameters or consumer perception. A study was designed to examine consumer perceptions of wines made from five different interspecific cold-hardy hybrid cultivars (Brianna, Edelweiss, La Crescent, Marquette, and Frontenac). These cultivars were chosen after a survey of industry members identified them as widely grown across the state. Four wines were selected for each of the cultivars to represent a range of wine styles. Chemical analyses were performed for all the wines and it determined that many of the wines had higher acidity and protein concentrations as compared to average Vitis vinifera L. concentrations. Consumer participants evaluated the wines based on a 7-point hedonic scale. These scores were statistically evaluated alongside the chemical parameters of the wines to understand if any of the parameters were impacting consumer liking. Correlations were weak between liking scores and chemical analysis; however, participants preferred wines containing high residual sugar (>30 g/L). Cluster analysis allowed for the grouping of consumers into 5 groups indicating that there were groups that had strong preferences for different varieties and/or styles. One of the parameters that was examined in the chemical analyses was tannin, and it was observed that the ‘Marquette’ and ‘Frontenac’ wines had very low tannin concentrations in comparison to V. vinifera wines. Tannin concentration is directly correlated to astringency perception, and therefore mouthfeel, which is an important quality factor of red wine. Low tannin concentrations in wines made from hybrid cultivars have been previously correlated to high protein concentrations in these grape cultivars and resulting wines. To modulate final wine tannin in Marquette wines, blending of this cultivar with a high tannin (low protein) cultivar, Cabernet Sauvignon, was performed at varying ratios of the two cultivars. The timing of blending was also examined by blending must (co-fermentation) or blending wine (post-fermentation). The tannin concentration of the different wines was examined to increase in a linear fashion as the concentration of ‘Cabernet Sauvignon’ was increased. Conversely, the protein concentration, as measured by SDS-PAGE, did not decrease linearly as ‘Cabernet Sauvignon’ increased. The loss of protein due to tannin was modelled through the Freundlich Isotherm, suggesting that the protein-tannin interaction is cooperative in nature. Overall, the post-fermentation blending was more successful than co-fermentation to increase tannin in wines made with ‘Marquette’ and ‘Cabernet Sauvignon’ grapes. To further understand the extraction and retention of tannin from interspecific cold-hardy hybrid cultivars the effect of juice versus mesocarp was evaluated for their abilities to adsorb tannin from an added tannin solution made from a commercial grape tannin. Three cultivars were evaluated, including two hybrids (Marquette and Frontenac) and one low tannin V. vinifera (Pinot noir). The mesocarp fraction showed low tannin recovery compared to the juice fraction (e.g., 24% vs. 70% for Marquette) for all cultivars. Protein from the supernatant of each fraction was measured for ‘Marquette’, and it was determined that the soluble protein could not be responsible for the difference between the two fractions. Therefore, the mesocarp fraction is postulated to have insoluble cell membrane proteins that significantly contribute to this adsorption. Future experiments will quantify this protein in the mesocarp fraction. Another cultivar like Cabernet Sauvignon will also be tested to understand if high tannin cultivars have a similar outcome for tannin recovery between a juice or mesocarp fraction. Through all these experiments, it has been shown that the chemistry of Iowa wine made from these interspecific cold-hardy cultivars is complex and consumer perceptions are not easily described by wine chemistry parameters alone. Expanding on this research to better understand these cultivars before, during and after fermentation is important to advancing the Iowa and Midwest grape and wine industries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".