Investigation of the Volatile Composition of Pinotage Wines Fermented with Different Malolactic Starter Cultures Using Comprehensive Two-Dimensional Gas Chromatography Coupled to Time-of-Flight Mass Spectrometry (GC×GC-TOF-MS)
Bibliographic record
Abstract
Headspace solid phase microextraction in combination with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (HS-SPME-GC × GC-TOF-MS) was used for the detailed investigation of the impact of malolactic fermentation (MLF) using three commercial Oenococcus oeni strains on the volatile composition of Vitis vinifera cv. Pinotage wines. GC × GC allowed the identification of 115 volatile compounds, including both major constituents and trace-level compounds, in a single analysis. A number of compounds differing in mean concentration levels between the control wines and those fermented with different starter cultures were shown for the first time to be influenced by MLF and/or the bacterial strain. Principal component analysis (PCA) provided excellent separation between the wines fermented with different MLF starter cultures and the control wine. Significantly different levels for some volatile compounds in wines fermented with one of the LAB starter cultures could be indicative of metabolic differences of this strain.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".