Carbohydrate Enrichment in In-Vitro Civet Coffee Fermentation: Impact on Arabica Coffee Beans
Bibliographic record
Abstract
This study aimed to evaluate the performance of in-vitro fermentation processes on civet coffee, employing a mixed-microbial enrichment culture, and to assess its impact on the physicochemical properties of the fermented product.Arabica Coffee cherries were utilized as the subject in this investigation.The inoculum, derived from civet fecal suspensions, was enriched through the augmentation of various carbohydrates, including soluble (e.g., glucose) and insoluble (e.g., starch) carbohydrates, mirroring the primary components present in civet food.Over an incubation period of four hours, a drop in pH from 7.0 to 5.6 was observed in the cultures, and volatile fatty acid (VFA) was detected at 2.8 mmol/L.It was found that the sugar conversion rate during in-vitro coffee fermentation by the starch-consuming microbial culture (2.1 mM/hour) significantly outperformed that of the glucose-consuming culture (0.9 mM/hour).The caffeine content in in-vitro fermented coffee (0.27-0.28 mg/100g) was found to closely approximate that of in-vivo fermented coffee via civet digestion (0.254 mg/100g).Notably, both in-vitro and in-vivo fermentation yielded caffeine content substantially lower than that of conventionally fermented coffee, which ranged between 1.5 and 2.7 g/100 g.In summary, the fermentation of Arabica coffee cherries using a mixed microbial culture, enriched with starch supplementation (SCM), demonstrated a faster rate compared to a culture enriched with glucose (GCM).The findings provide important insights for optimizing invitro civet coffee fermentation processes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".