Proteomic analysis of higher & lower altitude cultivars of Coffea arabica reveals differences related to environmental adaptations and coffee bean flavour
Bibliographic record
Abstract
Coffee ranks among the most popular beverages worldwide and is an important commodity in developing nations. While coffee beans harvested from Coffea arabica are considered to have a superior rich and balanced flavour, they are susceptible to disease and climatic variables like temperature, precipitation, and oxygen availability, each of which varies with altitude. We performed a comprehensive proteomic comparison of two C. arabica cultivars, the high-altitude Rwanda Shyira (RS) and the lower-altitude Brazil Flor de Ipe (BFDI), using liquid chromatography MS/MS analysis. Five of the identified 531 proteins exhibited statistically significant differences in expressional intensity between the two cultivars. These differences may correspond to bitter flavonoid concentrations along with adaptations to cold, hypoxic, and disease stressors at different altitudes and geographic niches. These substantial proteomic differences identified between these elevations provide a greater understanding of the effects of altitude on the C. arabica plant and its coffee, which has implications for the global market.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".