Lucerne common leaf spot: forage quality, photosynthesis rate and field resistance
Bibliographic record
Abstract
Effects of lucerne ( Medicago sativa ) common leaf spot caused by Pseudopeziza medicaginis on contents of the major nutrient components and leaf photosynthesis rate were studied. Disease resistance of 85 lucerne varieties (populations), 5 Medicago varia varieties (populations) and 4 M. falcata varieties (populations) was evaluated under alpine grassland conditions. Compared to the healthy leaves the crude protein content in the diseased leaves were reduced by 25%. A significant negative correlation between the crude protein content and the disease severity was found ( r =0.965, P 0.01). Leaf photosynthesis rate decreased as the disease severity increased. The photosynthesis rate was reduced by 48% when 13% of the leaf area was infected by the pathogen, whereas 84.1% of reduction was found when 85% of the leaf area was infected. Among 94 varieties (populations) evaluated for disease resistance only one of Rambler populations was immune. Ten lucerne varieties (populations) and another Rambler population were found highly resistant to common leaf spot, which included Baron and Apex from Canada, Wiscosin from the USA, and Xingping, Wugong, Zhaodong from China. The remaining 83 varieties (populations) were susceptible to the disease, which included 78 15 from the USA, Atlantic from Canada, Hetian and Xianyang from China, and M. falcata from Inner Mongolia, China.
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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".