Characterization of puccinia recondita, the causal agent of brown rust: a review
Bibliographic record
Abstract
Brown rust caused by Puccinia recondita is a significant disease in cereal growing areas worldwide.On average, brown rust can cause yield losses from 10% to 40% resulting in economic losses.The disease damages the leaves, stems and glumes of cereals.Classification of the pathogen causing brown rust has undergone several revisions.There are two different opinions about the causal agent causing brown rust on rye and wheat.Some scientists consider that the causal agent of brown rust in wheat (Triticum aestivum L.) and rye (Secale cereale) is included in the broad species of P. recondita defined by Cummins, but other scientists consider that there are two species causing brown rust -P.recondita in rye and P. triticina in wheat.There are many studies about the races of P. recondita in wheat: in North America, 70 races are collected every year; in Canada, 35 races have been found; in Europe, 105 races have been found.Unfortunately, there are no studies about the races of the pathogen of rye.P. recondita is a heteroecious fungus with a complicated life cycle.For successful development, the fungus requires cereals as primary hosts and different alternative hosts, depending on the specialization of the pathogen.Specific studies about the biology, distribution and harmfulness of Puccinia recondita in Latvia are necessary.Monographic method was used for this study.The aim of this article is to summarize the information from the literature about Puccinia recondita, the causal agent of brown rust, with emphasis on the occurrence, harmfulness, taxonomy, and life cycle of P. recondita f. sp.secalis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| 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".