Genotype‐by‐Environment Interaction and Trait Associations in Two Genetic Populations of Oat
Bibliographic record
Abstract
Ideal milling cultivars of oat (Avena sativa L.) should have high grain yield, groat percentage, β‐glucan, and protein but oil content lower than certain level. The genotype‐by‐environment interaction (G × E) of these traits and their genetic correlations were studied using two genetic populations (‘Goslin’ crossed with ‘HiFi’ and ‘Sherwood’ crossed with ‘HiFi’) tested in multilocation trials from 2010 to 2012 in eastern Canada. The results showed limited G × E for all of the quality traits, especially for β‐glucan and oil, and transgressive segregation was observed for all traits in both populations except for groat percentage in the Goslin × HiFi population. The G × E for grain yield was overwhelming, however, suggesting that yield must be selected within subregions. Four unfavorable trait associations were observed, namely, a negative correlation between grain yield and protein content, a positive correlation between β‐glucan content and oil content, a negative correlation between groat percentage and β‐glucan content, and to a lesser extent, a negative correlation between grain yield and groat percentage. However, the magnitude of these correlations was small and breeding lines with good levels of groat, β‐glucan, oil, and protein were identified. These lines may be used as parents in breeding superior milling oat cultivars.
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 | 0.000 |
| 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".