Genotype, environment and G × E interaction influence (1,3;1,4)‐β‐<scp>d</scp>‐glucan fine structure in barley (<i>Hordeum vulgare</i> L.)
Bibliographic record
Abstract
BACKGROUND: The structure of β-glucan influences its use in cereal-based foods and feed. The objective of this study was to determine the effect of environment (E) and genotype (G) on β-glucan fine structure and its genetic control in two-row spring barley with normal starch characteristics. RESULTS: A population of 89 recombinant inbred lines, derived from the cross of two-row spring barley genotypes Merit × H93174006 (H92076F1 × TR238), was characterized for concentration and structure of grain β-glucan in two environments. Results showed that concentrations of β-glucan, DP3, DP4 and DP3 + DP4 were positively correlated with each other, suggesting no preference for DP3 or DP4 subunit production in high- or low-β-glucan lines. The concentrations of β-glucan, DP3, DP4 and DP3:DP4 ratios were significantly influenced by genotype and environment. However, only DP3:DP4 ratio showed a significant effect of G × E interaction. Association mapping of candidate markers in 119 barley genotypes showed that marker CSLF6_4105 was associated with β-glucan concentration, whereas Bmac504 and Bmac211 were associated with DP3:DP4 ratio. Bmac273e was associated with both β-glucan concentration and DP3:DP4 ratio. CONCLUSION: The grain β-glucan concentration and DP3:DP4 ratio are strongly affected by genotype and environment. Single-marker analyses suggested that the genetic control of β-glucan concentration and DP3:DP4 ratio was linked to separate chromosomal regions on barley genome. © 2016 Society of Chemical Industry.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".