Projection of Robusta Coffee's Climate Suitability for Sustainable Indonesian Coffee Production
Bibliographic record
Abstract
This study aims to analyze the impact of climate change on the climate suitability of Robusta coffee in five main Indonesian coffee production centers namely Aceh, North Sumatera, South Sumatera, Bengkulu and Lampung using the Maxent approach. The study used climate data, and climate projections from Worldclim and coffee location data from maps of Indonesia's main agricultural commodities. The results showed that Maxent had good performance in modeling the climatic suitability of Robusta coffee at the provincial level, and the corresponding production areas shifted with different patterns between provinces. The areas with suitable and highly suitable climates for Robusta coffee were projected to decrease in all provinces except for Bengkulu. The findings suggest a future challenge for Robusta coffee sustainability in Indonesia. Aceh, North Sumatera, South Sumatera, and Lampung need to develop adaptation strategies to anticipate the increasingly unsuitable environment. On the other hand, Bengkulu can be considered a new area for coffee plantation. The projection of the suitability of the coffee climate is crucial in determining the future coffee development areas and for the rejuvenation of the existing coffee plantations, highlighting the significance of the study's findings for policymakers, farmers, and other stakeholders.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| 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".