A new method for assessing plant lodging and the impact of management options on lodging in canola crop production
Bibliographic record
Abstract
Lodging, defined as the permanent displacement of aboveground parts, is a common problem to cause yield loss, deterioration in seed quality and difficult to harvest in canola (Brassica napus L.) crop production. This study aimed to develop a method for assessing crop lodging, to examine how agronomic practices affected the relationships between root lodging and electrical capacitance traits. Canola plants were more susceptible to root lodging than stem lodging. The electrical measurements were more closely related with anchorage strength (Sp) than stem bending strength (Ss). Among the three electrical measurements, the root capacitance (C) displayed the most consistent and significant relationships with Sp in all three field experiments (R(2) = 0.88-0.56; P ≤ 0.01). This study indicates that the risk of lodging can be reduced by using appropriate management practices and variety selection. Enhancing root Sp was advocated as a priority over enhancing stem Ss in cultivar improvement. Electrical measurements, especially of root C, can be considered as a non-invasive technique that could partially replace the intrusive methods used for the in situ assessment of lodging resistance among various agronomic practices or can be applied in breeding programs for selecting genotypes with high yield potentials and strong Sp values.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".