Effect of Simultaneous Inoculation with Yeast and Bacteria on Fermentation Kinetics and Key Wine Parameters of Cool-Climate Chardonnay
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Bibliographic record
Abstract
Inoculating grape musts with wine yeast and lactic acid bacteria (LAB) concurrently in order to induce simultaneous alcoholic fermentation (AF) and malolactic fermentation (MLF) can be an efficient alternative to overcome potential inhibition of LAB in wines because of high ethanol concentrations and reduced nutrient content. In this study, the simultaneous inoculation of yeast and LAB into must was compared with a traditional vinification protocol, where MLF was induced after completion of AF. For this, two suitable commercial yeast-bacterium combinations were tested in cool-climate Chardonnay must. The time courses of glucose and fructose, acetaldehyde, several organic acids, and nitrogenous compounds were measured along with the final values of other key wine parameters. Sensory evaluation was done after 12 months of storage. The current study could not confirm a negative impact of simultaneous AF/MLF on fermentation success and kinetics or on final wine parameters. While acetic acid concentrations were slightly increased in wines after simultaneous AF/MLF, the differences were of neither practical nor legal significance. No statistically significant differences were found with regard to the final values of pH or total acidity and the concentrations of ethanol, acetaldehyde, glycerol, citric and lactic acids, and the nitrogen compounds arginine, ammonia, urea, citrulline, and ornithine. Sensory evaluation by a semiexpert panel confirmed the similarity of the wines. However, simultaneous inoculation led to considerable reductions in overall fermentation durations. Furthermore, differences of physiological and microbiological relevance were found. Specifically, we report the vinification of "super-dry" wines devoid of glucose and fructose after simultaneous inoculation of yeast and bacteria.
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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 it