Breeding Programs Against Coffee Leaf Rust in Brazil: A Review
Bibliographic record
Abstract
Leaf rust caused by Hemileia vastatrix Berk & Br. is the main disease that attack coffee plants all over the world. The disease causes 35-50% of yield loss in average in Brazil. The disease is present in all the countries that cultivate coffee (Coffea arabica L. and C. canephora L.). Resistance of coffee to leaf rust is the main method of disease control. But the great variability of the pathogen makes it very difficult. In the world and in Brazil there are more than 50 and 16 races of the pathogen, respectively. In Brazil there are seven research institutions that have been working with breeding programs against coffee leaf rust. The main source of resistance to coffee leaf rust used by all the research institutions in Brazil came from ‘Centro de Investigação das Ferrugens do Cafeeiro-CIFC’ in Oeiras, Portugal. They are: Híbrido de Timor (HdT) CIFC 832-1 and HdT CIFC 832 and HdT CIFC 2570. Crosses were made at CIFC with a variety Caturra and Vila Sarchi and sent to Brazil, Colombia and some countries of Central America and Caribean. The countries that received the germplasm of CIFC back crossed them with varieties Catuai and Mundo Novo. Crossing HdT with Caturra originated the group Catimor and HdT with Vila Sarchi the group Sarchimor. Other source of resistance to leaf rust came from Coffea canephora crossed with C. arabica originating the cultivar Icatu. But the great majority of the resistant cultivar came from Catimor and Sarchimor. More than 50 coffee varieties have been launched with resistance to the leaf rust in the last 40 years in Brazil. But only few of them remain with vertical resistance to all the races of H. vastatrix. Horizontal resistance is more common on C. canephora var. conilon and C. canephora var. robusta than in C. arabica. This revision has the purpose to relate to the scientific comunity the breeding programs against coffee leaf rust in Brazil.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".