The source material of soft spring wheat for improving the quality of grain and resistance to lodging
Bibliographic record
Abstract
The Northern Trans-Urals is a region of intensive agriculture that needs high-yielding varieties that are resistant to lodging and a-biotic environmental factors, forming high-quality grain. In this respect, as a starting material for breeding, Canadian varieties with good technological indicators of grain and Norwegian varieties with high resistance to lodging and well-expressed economic and valuable characteristics are of interest. An important indicator when creating wheat varieties is the resistance to pre-harvest germination of grain on the root. The conjugacy of this feature with the yield is high and is expressed negatively - r = -0.922. Among the studied cultivars, Demonstrant (Norway) and 5603HR (Canada) stand out for their resistance to grain germination in the ear. Norwegian varieties are characterized by multi-grain ear, fine grain and compacted ear. Marker traits of drought resistance – the length of the upper internode and the removal of the ear, are better expressed in the standard of Omskaya 36, varieties of local selection and varietals - Laban and GN 06600 (Norway). In arid conditions, these varieties have a more pronounced yield. The best in this respect is Kazakhstan one - Astana (2.27 t/ha). The intensity was highlighted by the variety - GN 06600 (Norway) - 5.05 t/ha. The revealed conjugate relationships in the studied traits allow to purposefully conduct breeding work.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.010 |
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".