Validating the contributions of stem and root traits to barley lodging in western Canada
Bibliographic record
Abstract
Lodging caused by stem buckling or root anchorage failure results in significant economic losses each year globally due to increased disease load, downgrading of quality, and yield loss. To increase lodging resistance in western Canadian barley, a study was undertaken to identify traits associated to lodging score. Mechanical and architectural traits encompassing whole plant, stem and root features of 13 spring barley genotypes, representing a diversity of classes, height, and lodging resistance, were evaluated at six field locations over three years. Correlation analysis identified plant height, internode length, crown root angle and root system solidity as traits with the largest influence on lodging (r = 0.37, 0.27, -0.32 and 0.62, respectively). A structural equation model (SEM) was created to further evaluate which traits had direct or indirect influence on barley lodging. The best fitting SEM included nine traits that captured aspects of the whole plant, stem and root system. Plant height (effect estimate = 0.46) and root system solidity (0.14) showed a direct influence on lodging, while root angle had both direct (-0.21) and indirect (via height) influence on lodging. Stem strength, stem outer diameter, and stem volume had indirect effects on lodging through height, while root network area, convex area and total root length had indirect effects on lodging through root system solidity. The three traits that directly influenced lodging in both correlation analysis and SEM, plant height, root angle, and root system solidity, displayed moderate to high heritability (0.85, 0.78 and 0.57, respectively), thus making them suitable for breeding selections. Collectively, this study confirmed the role of plant height and root angle in lodging, identified root system solidity as a novel trait associated to barley lodging resistance, and revealed root imaging as a new screening tool to help breeders select for, and improve, lodging resistance in the absence of observable field lodging.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".