Assessing Estonia’s viticultural potential based on the compositional analysis of sugars and acid compositional analysis of wine grape cultivars
Bibliographic record
Abstract
The primary objective of this study was to assess Estonia’s potential for viticulture through the calculation of the Heliothermal Index and analysis of its 20-year dynamics. The secondary objective was to determine the variability in grape sugars and acids composition depending on vintage (2023, 2024) and cultivar characteristics in ‘Solaris’, ‘Regent’, ‘Leon Millot’, ‘Cabernet Cortis’, ‘Marquette’, ‘Hasansky Sladky’, ‘Zilga’, and ‘Rondo’. Over the twenty years, the Heliothermal Index ranged from 872 to 1622, showing a warming trend with implications for viticultural potential. Fructose content in grapes ranged from 72 to 98 g l⁻¹, with ‘Marquette’ having the highest and ‘Zilga’ the lowest. Glucose content was lowest in ‘Zilga’ (64 g l⁻¹) and highest in ‘Marquette’ (98 g l⁻¹). ‘Zilga’ had the highest tartaric acid content (5.9 g l⁻¹), while ‘Leon Millot’ (3.5 g l⁻¹) and ‘Regent’ (3.7 g l-1) had the lowest. ‘Hasansky Sladky’ had the highest malic acid content (5.5 g l⁻¹), while ‘Regent’ (2.1 g l⁻¹) and ‘Solaris’ (2.5 g l⁻¹) had the lowest. The study confirmed that the tested cultivars are suitable for producing dry wine in Estonia, which belongs to the EU viticulture zone A.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.007 |
| Science and technology studies | 0.001 | 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".