Effects of seed size and seed weight on seedling establishment, vigour and tolerance of Argentine canola (<i>Brassica napus</i>) to flea beetles, <i>Phyllotreta</i> spp.
Bibliographic record
Abstract
A 3-yr study was conducted on four Brassica napus L. cultivars to determine the effects of seed size and seed weight on the performance and tolerance of canola seedlings to feeding damage by flea beetles, Phyllotreta spp. (Coleoptera: Chrysom elidae). Seed lots of a doubled haploid cultivar Cyclone, hybrid cultivar AC H102 and two open-pollinated cultivars Profit and AC Elect were sieved to obtain small, medium, large and very large seeds (1.4–1.6, 1.6–1.8, 1.8–2.0 and 2.0–2.2 mm diameter, respectively). Under controlled environmental conditions, leaf area, shoot weight and biomass of seedlings from large and very large seeds were 1.3–2.0 times greater than those of seedlings from small seeds. Under field conditions without insecticides, seedlings from small seeds of each cultivar had the highest flea beetle damage, poorest establishment, and lowest shoot weight, biomass and yield. Compared with small seeds, large seeds improved seedling establishment, shoot weight, biomass and yield by 1.1, 1.6–2.0, 3.0–3.5 and 1.5 times, respectively. Results indicated that seedlings from large seeds are more vigorous and tolerant to flea beetle damage than seedlings from medium or small seeds. Seedling vigour and tolerance was due to a higher initial shoot biomass and higher growth rate when flea beetle damage was severe. When damage exceeded 50%, large heavy seeds had the best stand establishment, best shoot growth and highest yield in each cultivar. Key words: Canola, flea beetles, seed size, seed weight, seedling vigour, tolerance
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) | 0.001 | 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".