Races of Hemileia vastatrix and Variation in Pathogenicity of Colletotrichum kahawae Isolates to Compact Coffee Genotypes in Tanzania
Bibliographic record
Abstract
Eighteen clones of coffee rust differentials were used to characterize rust races prevailing in the coffee growing areas in Arusha, Kilimanjaro, Mara, Bukoba, Kigoma, Mbeya and Ruvuma regions. The results showed the presence of seven new Hemileia vastatrix races causative agent for coffee leaf rust (CLR) in the surveyed coffee growing areas. The races were: XLI (v2, 5, 8), XLII (v2, 5, 7, 8 or v2, 5, 7, 8, 9), XV (v4, 5), XXX (v5, 8), XXXIII (v5, 7 or v5, 7, 9), XXXIV (v2, 5, 7 or v2, 5, 7, 9), XXXIX (v2, 4, 5, 6, 7, 8, 9). Four strains of Colletotrichum kahawae originating from 4 coffee ecosystems were used to test their level of pathogenicity on 16 compact coffee genotypes, Ctr088 and commercial variety N39. The four C. kahawae strains were less pathogenic to six compact coffee genotypes; CVT2, CVT4, CVT5, CVT7, CVT8 and CVT13, completely nil pathogenic to Ctr088, but significantly highly (P < 0.05) pathogenic to N39. Coffee genotype Ctr088 was confirmed to be a potential donor of developing coffee berry disease (CBD) varieties with durable resistance. Differential interaction between the compact genotypes and the four C. kahawae strains needs further investigation.
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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 | 0.000 | 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".