Stem and canopy attributes that affect lodging resistance in lentil
Bibliographic record
Abstract
Many lentil (Lens culinaris L.) cultivars currently grown in Western Canada are susceptible to lodging. The objective was to determine if plant traits associated with lodging but independent of environmental influences could be used for indirect selection of lodging resistance. For a range of canopy variation, eight genotypes were grown at three plant population densities in the field in 2001 and 2002 at five locations. Four unadapted genotypes (designated FLIP), varying in plant profile and stem stiffness, were compared with locally adapted cultivars. Lodging is a complex trait and was influenced by both genetic differences among the genotypes and environmental conditions. Large green market class cultivars had weak stems and lodged easily. As the canopy’s ability to recover from crushing increased, lodging increased due to greater plant biomass. The greater the fiber content in the plant stems, the more biomass and more lodging occurred. Genotypic ranking of stem diameter was consistent across locations, and stem diameter may be used to indirectly select for lodging resistance. From regression analysis, stem diameter and lodging were described by branch number, recovery from canopy crushing, plant density, height, stem fiber content and lignin content; branch number, plant density and plant height were the most influential terms. For screening lodging resistance in crosses made from a lodging resistant genotype and a highly lodging susceptible genotype, selection of progeny with the smallest stem diameter should be the most lodging resistant, although yields will be reduced. Selection procedures would involve seeking large diameter stems but with similar stem traits of the small-stemmed FLIP lines. Key words: Lodging, stem diameter, biomass, branch, lentil, fiber
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".