Evaluation of barley genotypes for the content of β-glucans in grain and other valuable features in Eastern Siberia
Why this work is in the frame
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Bibliographic record
Abstract
Background.The aim of the research was to identify barley germplasm accessions with the minimum and maximum content of β-glucans in their grain in combinations with other improved useful traits. Material and methods.The material for analysis were 18 hulled and 8 naked barley accessions of various ecogeographic origin from the collection of the N.I. Vavilov AllRussian Institute of Plant Genetic Resources (VIR), which were grown under the conditions of Eastern Siberia in 2016–2018. Results.Hulled accessions yielded grains with β-glucan content from 3.18 to 4.51%; naked ones, from 3.18 to 5.21%. According to the minimum value of the studied qualitative trait (3.18–3.43%), cultivars of Siberian breeding were identified: ‘Mayak’ (k-29622, Krasnoyarsk Territory) and ‘Tarsky 3’ (k-30719, Omsk Province), plus cv. ‘AC Albright’ (k-30599, Canada); according to the maximum value (5.06–5.21%), the naked accessions Nudum 155 (k-13328, Ukraine) and ‘Nudum 95’ (k-31125, Chelyabinsk Province). The highest protein content in grain (16.63–18.36%) was found in the accessions Nudum 155, Nudum 7566 (k-29453, Kyrgyzstan) and ‘Nudum 95’. The accessions Nudum 155 and ‘Nudum 95’ were characterized by combined high contents of β-glucans and protein in their grain. Early maturity and increased productivity were shown by the cultivars ‘Tarsky 3’, ‘Kolchan’ (k-31039, Altai Territory), ‘Zolotnik’ (k-30845, Altai Territory), ‘Abalak’ (Krasnoyarsk Territory, Tyumen Province), and ‘AC Albright’ (Canada). A significant positive relationship was found between the content of β-glucans and the weight of 1000 grains in both forms of barley. Conclusion.According to β-glucan content combined with other valuable characteristics in grain, the accessions ‘Mayak’, ‘Tarsky 3’ and ‘AC Albright’ are of interest for the improvement of fodder cultivars, while ‘Nudum 95’ and Nudum 155 are promising for breeding for food.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it