SNOW MOLDS: HISTORY OF THE STUDY AND CONTROL (review)
Bibliographic record
Abstract
Snow mold is caused by pathogenic low-temperature fungi and fungi-like pathogens which can attack grassy winter and perennial plants and even woody plants. Pathogens infect crops in autumn and develop under snow and early in spring at low temperatures. History of the emergence of the terminology for pathogenic low-temperature fungi, the appearance of the «snow mold» terms and domestic «vyprevaniye» (eng. «dumping-off») are represented, and various snow molds and their pathogens in Russia are described. Recent advances in agrochemical, chemical, biological and breeding technologies used to provide snow mold control are under consideration in detail, particularly data obtained in North America (USA, Canada), North Europe (Sweden, Norway, Finland), Asia (Japan) with special attention to the investigations in Russia. Crop rotation using crops being not the host plants of these pathogens and thus resistant to them is considered as rather effective agrotechnology decreasing plant damage from snow molds, and also deep tillage, early or late sowing, show thawing by its covering with black materials, monthly use of some composts are also discussed. Seed sterilization against Microdochium nivale infection is widely used in North Europe. In Russia the Baytan, Benlat, Granoza and Pentiuram are used on winter crops against Typhula incarnata and T. idahoensis (syn. T. ishikariensis). Fungicides are economically effective in the years of strong damage from snow molds, at that, pathogenic species differ in sensitiveness to fungicides. Characteristics of definite fungicides used are discussed. Biological suppression also is a method for anti-snow mold protection. For the purposes, the antagonistic agents effective in summer when snow molds are dormant, as well as low temperature agents active in the period of snow mold development can be used. Natural suppressors such as composts and antagonistic organisms were successful against Typhula spp. No special breeding for plant resistance to snow molds was carried out in Russia until recent time, nevertheless, in numerous investigations some grain crop species resistant to snow mold have been revealed. Particularly, by immunological assessment of 500 specimens from the VIR World Collection (N.I. Vavilov All-Russian Institute of Plant Industry, St. Petersburg) and domestic varieties the resistant forms are described as follows: Shatilovskaya tetra, Populyatsiya I-82 tetrs, Sibirskaya krupnozernaya, Taezhnaya, Kirovskaya 89, Vyatka 2, Dymka, Rosinka, Ilim, Falenskaya 4, Purga, F4-92, Chulpan 3, Korotkostebel’naya 6, Khar’kovskaya 88, Tatarskaya 1, Bezenchukskaya 88, Volkhova, Takovskaya 29; LAD-287 St-2614, Antonnisnie, Leelondzkie Kartowe 1 1, Leelondzkie Krotnoslomix 1⁄2 Baltycnie (Poland), Epos, Rerus (DDR), Inzucht 74/2, Inzucht 108/8 (Sweden), к-10953 (Finland), Feniks (Belgium), к-11385 (Yugoslavia), к11150, к-11389 (Portugal), к-11306 (Argentina), к-11179, к-11180 (USA), к-11388 (Tajikistan), к11398 (Georgia), к-11131 (Azerbaijan), Belta tetra (Belarus), Beve (Ukraine).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".