Root traits and biomass production of drought‐resistant and drought‐sensitive arabica coffee varieties growing under contrasting watering regimes
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Drought is a major factor affecting coffee production, and different genotypes exhibit varying degrees of resistance to drought stress. We examined root traits and biomasses of drought‐resistant (74110, Angafa, Bultum, Chala, and Gawe) and drought‐sensitive (75227, Koti, Melko CH2, Menasibu, and Mokah) Coffea arabica varieties at seedling stage under contrasting watering regimes (water stressed and well watered) for 30 days followed by 15 days of recovery to identify the association between drought resistance and root traits and dry matter partitioning, and the impact of drought stress on growth performance of arabica coffee varieties. We used a split‐plot design with three blocks, where watering regime was the whole‐plot factor and variety was the subplot factor. During water‐stress and recovery periods, the interaction effect between watering regime and variety significantly affected root traits and dry matter partitioning, while the watering‐regime main effect affected biomass. We observed a higher (1) tap root diameter (0.34 cm), lateral root number (80.7), and root volume (4.7 cm −3 ) for 74110; (2) lateral root number (79.3), specific root length (24.8 cm g −1 ), and root‐mass ratio (0.41 g g −1 ) for Bultum; and (3) root length density (3.3–5.2 cm cm −3 ), root angle (42.6°–47.8°), root‐mass ratio (0.40–0.42 g g −1 ), and root‐shoot ratio (0.67–0.72 g g −1 ) for Angafa, Chala, and Gawe under water‐stressed condition. During both study periods, biomasses were much lower under water‐stressed than under well‐watered condition. The findings show the association between drought resistance and root traits and dry matter partitioning, and the impact of drought stress on growth performance of young arabica coffee.
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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 | 0.001 | 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 | 0.001 |
| 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