Powdery Mildew is a Dangerous Disease of Spring Triticale in the Far East
Bibliographic record
Abstract
Abatract The studies were carried out in 2015–2022 with the goal of determining a degree of powdery mildew-induced damage to collection samples of spring triticale in the soil and climatic conditions of the Khabarovsk krai of the Far East. Eighty four samples of various ecological and geographical origins were studied. The weather conditions during the observation period were contrasting; at a norm of precipitation for April to August of 466 mm, an excess reaching 16 to 263 mm. Waterlogging contributed to an increase to 100% in the relative air humidity. The experimental site had a heavy loamy meadow-brown podzolized-gley soil. The distribution (R) of powdery mildew in triticale crops was high (80–100%), and the annual intensity of development (P) reached epiphytotic values. Collection varieties of spring triticale were assigned according to the intensity of the disease development: moderately susceptible (13 samples), susceptible (35 samples), and highly susceptible (36 samples). High correlation coefficients (r = 0.861–0.897) were found between the amount of precipitation in the booting-earing phase and the degree of plant powdery mildew-induced infection. A compiled linear regression equation demonstrated a dependence of the intensity of development of the powdery mildew pathogen and the amount of precipitation in the second ten days of June. The following spring triticale varieties had moderate susceptibility to powdery mildew pathogens (P = 30–40%): Amore, Saur, Prag 409, Dagvo (Russia), Lana, Lotos (Belarus), Zgurivskiy, Oberig Kharkovskiy (Ukraine), 70 HN 458 (Canada), Je 57 (USA), Anoas 5, MX 51 (Mexico), and Tleridal (Switzerland).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".