IMMUNOLOGICAL ASSESSMENT OF THE HULLED BARLEY COLLECTION ACCORDING TO ITS RESISTANCE TO LEAF DISEASES IN THE SOUTHERN PART OF THE ROSTOV REGION
Bibliographic record
Abstract
In the conditions of artificial infectious background of the laboratory of plant immunity and protection (Agricultural Research Center “Donskoy”) there has been conducted an immunologic estimation of hulled barley samples of ARIR collection. There has been estimated resistance to the following pathogens: powdery mildew (pathogen Erysiphegraminis f. hordei), barley net blotch (Pyrenophorateres (Died.) Drechsler [Drechslerateres (Sacc.) Shoemaker]) and barley dark-brown blotch (Bipolaris sorokiniana (Sacc.), Shoemaker [Cochliobolussativus (S. Ito &Kurib) Drechsler ex Dastur, Helminthosporiumsativum Pammel, C.M. King & Bakke]). The study of disease manifestation was done in 2016–2017. The results allow estimating variety resistance in the extreme infectious conditions similar to epiphytotinous conditions. As a result there have been identified the samples ‘Dublet’ (Belorussia), ‘Omsky golozerny 1’ (Russia), ‘К-26648’ (Pakistan), ‘Back CDC’,’CDC VC Ywire’, ‘CDC Dawn’ (Canada), ‘К-3038’ (Dai Mai), ‘Orgeniepetite’ (France), ‘NB-OWA’ (Nepal) and others that showed resistance and slight susceptibility to powdery mildew. The samples ‘Back CDC’, ‘Bowman’ (Canada), ‘84469/70’, ‘К-303’ (Dai Mai), ‘Dublet’ (Belorussia), Brunее (Ethiopia), ‘Orgeniepetite’ (France) and others showed resistance to barley net blotch. The samples ‘Dublet’, ‘Omsky golozerny 1’, ‘Omsky golozerny 2’, ‘Yudinsky 1’, ‘К-26648’, ‘84469/70’, ‘Orgeniepetite’, ‘CDC Dawn’, ‘NB-OWA’, ‘К-3038’, ‘CDC VC Ywire’, ‘E.E.B.N.46’ demonstrated a complex resistance to both pathogens and they are recommended for use in the breeding programs on immunity.
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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 | 0.001 | 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".