Results of phytopathological examination of soybean seeds obtained in the Biya-Chumysh zone of the Altai Region
Bibliographic record
Abstract
With increasing soybean production in the Altai Region, phytosanitary risks increase due to the spread of pathogens of various etiologies with seed material. Timely phytopathological examination of seed material helps to reduce financial risks and improve quantitative and qualitative indices of the yield. The research goal was to conduct phytopathological examination of soybean seed samples and determine the species composition of pathogens in the Biya-Chumysh zone of the Altai Region. Three soybean varieties were tested: Alberta, Fulford, and Yukon. The phytopathological examination of the seeds was conducted in the Altai Testing Laboratory of the Federal Center for Animal Health (FGBU VNIIZZH) in accordance with GOST 12044-93 using germination, microscopy, and morphological disease identification. The degree of seed infestation by variety over a three-year period was evaluated. Fusarium was found to be the most common phytopathogen present in all varieties throughout all years of the study with the level of damage varying by year. Bacteriosis was also the most common disease but it exhibits significant varietal specificity: the highest incidence was observed in the Alberta variety, while the lowest was observed in the Yukon variety. Downy mildew was detected exclusively in the Alberta variety indicating its genetic susceptibility to the pathogen and requiring regular phytosanitary monitoring. Thus, the phytopathological state of seeds is determined by the combination of weather conditions and varietal characteristics. Regular phytosanitary testing of seeds is essential to develop effective preventive and protective measures aimed at reducing risks and improving seed quality.
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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) | 0.000 | 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 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".