Interactions of Vine Age and Reflective Mulch Upon Berry, Must, and Wine Composition of Five<i>Vitis vinifera</i>Cultivars
Bibliographic record
Abstract
ABSTRACT Four- and 14-year-old Cabernet Franc, Cabernet Sauvignon, Pinot Meunier, Pinot noir, and 15-year-old Riesling vines located at Thirty Bench Vineyards in Beamsville, Ontario, were assessed in terms of vine age (2002 and 2003) and reflective mulch treatments (2003) with respect to berry, must, and wine composition as well as wine sensory attributes. In 2002, but not 2003, old vines had higher yields, clusters per vine, cluster weights, and berry weights than young vines. Berries from young vines tended to have higher Brix and lower titratable acidity (TA), pH, and total phenols than those from old vines in 2002; in 2003, age showed little impact on berry composition. Wines made from young vines in 2002 were higher in TA, and often lower in pH, color intensity, and anthocyanins than those from old vines, while in 2003, young vines produced wines with lower TA, and higher pH, intensity, and total phenols. Reflective mulch showed few effects on the berry, must, and wine composition of the red wine cultivars; however, mulch increased free and bound terpenes in the Riesling berries. Wines produced from young Cabernet Sauvignon and Cabernet Franc vines exhibited more intense vegetal aromas and flavors than those from old vines in 2002 but not in 2003. The red wines made from the mulched vines generally exhibited the least amount of vegetal aroma and flavor. Reflective mulch also led to less perceived acidity in Riesling wines.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".