Mycobiota of rape seeds in Romania. I. Identification of mycobiota associated with rape seeds from different areas of Romania
Bibliographic record
Abstract
The spectrum of fungal diversity associated with rape seeds belonging to 33 cultivars (Alaska, Astrada, Astrid, Atlantic, Betty, Champlein, Chayenne, Dexter, Digger, Elvis, Eurowest, Finesse, Herkules, Hydromel, Hydromel-MA, Ladoga, anitoba, Masa Rom, Milena, Mohican, Montego, Nectar, Ontario, Orkan, Perla (4 lots), Remy, Robust, Rodeo, Saphir, Tiger, Tiger CBC Lot ROM06-121-110, Triangle, Valesca, Vectra) and 2 hybrids (H-90-20-83, H-90-21-83) has been established by samples’ macroscopical and microscopical analizying, during 2006-2008, for the first time in Romania. The Ulster method on malt-agar and PDA culture media has been used, evaluating the percentage of fungal taxons present on/in rape seeds. The most important pathogenic fungi identified were: Sclerotinia sclerotiorum (Lib.) de Bary, Botrytis cinerea Pers., Rhizoctonia solani Kühn, Alternaria brassicae (Berk.) Sacc., A. brassicicola (Schwein.) Wiltshire and Fusarium spp. Also, a large quantities of some saprophytic fungi, as Alternaria, Cladosporium, Aspergillus, Penicillium, Rhizopus have been recorded. These ones have been affected the health condition of rape seeds, suppressing their germination and other vital phenomena. Among potential antagonistic fungi the following genera have been isolated: Chaetomium (0-4%), Trichoderma (0-10%), Aspergillus (0-14%), Penicillium (0-100%). Some correlations and comparisons have been established between fungal diversity, their provenience, cultivars, culture media (Malt-Agar/MA, Potato-Dextrose-Agar/PDA) used. It has been evaluated the behaviour of rape cultivars and hybrids towards the main rape seed pathogens.
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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 | 0.002 | 0.001 |
| 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".