Agrobiological features of the new naked oat variety Baget
Bibliographic record
Abstract
Oat grain is used both for forage and food aims. Therefore, it is so important to grow naked oat that is more processable due to the lack of husk. Ten varieties of naked oat are included into the State Register of the breeding achievements of Russian Federation, but only three of them are suitable for growing in the European part of the country. That is why the aim of the study is creation of productive variety of naked oat having high grain qualities which would be suitable for growing in different agro-climatic zones of European Russia. Studies were conducted according to the methods of state varietal testing in three ecological sites: Federal Agricultural Scientific Center of North-East (Kirov, 2000 - 2017), Falenki breeding station - Branch of FARC North-East (v. Falenki, Kirov region, 2012 - 2017), and Samara Agricultural Research Institute ( Bezenchuk, Samara region, 2015 - 2017). Naked oat variety Baget was created by method of individual selection from cross population ОА 503/1 (Canada) * Tumensky golozerny (Russia) with following control of trait in further generations. The variety is intended for production of food grain (children, diet, functional, and gluten-free nutrition) as well as for grain forage. In 2017 there were the most favorable growing conditions for the vegetation of Baget variety and comparison varieties Vyatsky and Bekas within 2015 - 2017 studies. Index of environment conditions (lj) in 2017 varied from 0.734 in Samara and 0.7507 in Falenki breeding station up to 1.8274 in FARC North-East. Average productivity of the new variety for years of study in ecological sites was 4.07 t/ha that is 0.45 t/ha higher than for standard Vyatsky and 0.36 t/ha higher than for oat variety Bekas. Analogous data were received in studies of 2012-2017 for ecological sites of Kirov region. Exceed of standard on productivity (3.86 t/ha) was 0.48 t/ha, that of variety Bekas - 0.33 t/ha.
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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 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".