Comprehensive evaluation of spring barley mutants according to their yield components
Bibliographic record
Abstract
Background. The need to increase the genetic diversity of barley (Hordeum vulgare L.) is determined by its value and cultivation scope, which is especially important in the context of the changing climate. Material and methods. The study was carried out in 2021 and 2022 at the experimental site of the Lake Kuchak biostation located in Nizhnetavdinsky District, Tyumen Province (57°20ʼ57.3”N, 66°03ʼ21.8”E). Mutant forms were obtained by treating seeds of accessions ʻZernogradsky 813ʼ, Dz02-129 and C.I. 10995 with solutions of the chemical mutagen phosphemide at concentrations of 0.002% (2·10–3 М) and 0.01% (1·10–2 М). The mutants of the fifth (M5) and sixth (M6) generations were evaluated for a set of traits valuable for breeding in comparison with the original forms and reference cultivars ʻAchaʼ and ʻAbalakʼ. The main productivity characters were analyzed in the laboratory, and breeding indices were calculated (ear potential index, Canadian index, ear linear density index, Mexican index, plant productivity index, and Finnish-Scandinavian index). Results and conclusion. Most of the studied mutants under moisture deficit and elevated temperature conditions were superior to the original forms in their productivity characters. Mutant plant samples with stable manifestation of those traits, irrespective of the growing season conditions, were selected. Assessment of the genotype–environment interaction using breeding indices made it possible to identify promising mutants for inclusion in breeding programs. Correlation analysis helped to identify indices closely related to grain yield: Canadian index (r = 0.85), Mexican index (r = 0.76), and plant productivity index (r = 0.70). They can be recommended for selection of stress-resistant barley forms.
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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) | 0.001 | 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".