Responses of Compact Coffee Clones Against Coffee Berry and Coffee Leaf Rust Diseases in Tanzania
Bibliographic record
Abstract
The utilization of resistant Arabica coffee (Coffea arabica) varieties is considered as the most economical control for coffee berry disease (CBD) and coffee leaf rust (CLR) in Tanzania. The resistance levels of varieties at field and laboratory conditions were assessed through their phenotypic disease reaction response to CBD and CLR. In this study sixteen (16) compact hybrids of C. arabica plus four (4) standard cultivars were evaluated under a range of environmental conditions in on-station and on-farm trials in Tanzania. Also four (4) Colletotrichum kahawae strains of the pathogen responsible for CBD infection; 2010/1, 2010/2, 2006/7 and 2006/14, and Hemileia vastatrix uredospores were used to test the sixteen (16) hybrids through artificial inoculation under controlled conditions (temperatures between 19 to 22 ºC, R. H. 100%). Results showed that a significant level of variability (P < 0.05) occurred between the sixteen (16) compacts, three (3) standard checks and N39 a commercial susceptible variety across trials. Compact genotype CVT14 (PNI086 x (N39 x Rume Sudan Selfed F2) showed resistance to the four strains of C. kahawae and Hemileia vastatrix. Differential reactions on compact genotypes were found to C. kahawae and H. vastatrix strains existing in different coffee growing regions in Tanzania; genotypes CVT4 (PNI088 x (SL34 x HdT) x Kent x Rume Sudan) and CVT13 (PRO127 x (Blue Mountain Jamaica x Cioccie) x Rume Sudan) showed partial resistance to C. kahawae strains 2010/1, the genotypes were susceptible to strains 2010/2 but resistant to strains 2006/7 and 2006/14. This shows that host response reaction can be used as criteria for varietal assessment when evaluated at different locations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".