Study of the parent material of soft winter wheat for breeding for grain quality
Bibliographic record
Abstract
The sources of valuable traits for targeted use in the breeding of new winter wheat varieties with improved quality traits are presented. The results of the evaluation of the parent material on the expression of economically valuable features in the collection samples of soft winter wheat are presented. The paper presents data on 31 varieties of different ecological and geographical origin. Field experiments were conducted in 2018-2020 in the breeding rotation under the conditions of the southern zone of the Rostov region. Quality indicators of the varieties: thousand grain weight, protein content, quantity and quality of gluten in the grain, grain unit, total vitreousness, baking properties were determined by standard methods and GOSTs. As a result of the clustering of varieties, it is shown that the breeding program to create adaptive varieties with high grain quality should include as basic parent material the varieties which are included in the 5th and 6th clusters L-19578 (Russia), Etana (Germany), Warwick (Canada), Akter (Germany), MV-15-09 (Hungary), Simonida (Serbia), GK Hollo (Hungary), Webster (Canada), Wisdom (Canada), No. 42 CIMMYT (USA), and KS 96 WGRC 37 (USA). These varieties showed good results in the southern zone of the Rostov region. The other varieties of the collection nursery are recommended to be included in the breeding work in accordance with the principle of complementarity, as mutually complementary varieties in the expression of a particular trait or property.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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".