Field pea seeding management
Bibliographic record
Abstract
The impact of seed placement and seeding rate on crop yield is not clearly understood for field pea (Pisum sativum L.). A field experiment was conducted at Melfort, SK, and Lacombe, AB, in 1998 and 1999, to evaluate the effect of three seed placements (distinct row: 23 cm and 30 cm with a hoe opener; and spread band: a 20-cm spread using a 28-cm sweep on a 23-cm row spacing) and three seeding rates (50, 100, and, 150 seeds m-2) on pea seedling density, seed yield and seed weight of a leafy prostrate and semi-leafless upright cultivar. A follow-up experiment was conducted at seven sites across Saskatchewan in 2001 to further examine the influence of a wider range of seeding rates (20, 30, 40, 50, 60, 70, 80, 90, 100, and 120 target plants m-2). Pea productivity for both cultivars was not affected by the different seed placements, despite a 4 mg greater seed weight for distinct row seed placements compared with spread band placement across all 1998–1999 sites. Moreover, the absence of a seed placement by seeding rate interaction indicated that greater spacing between plants was not associated with improved pea yield when seeding rate was increased, regardless of the cultivar. Yield component compensation occurred where increased plant density from higher seeding rates reduced seed weight. In the 2001 study, seed yield benefits were small at seeding rates greater than 50 target plants m-2. There was a tendency for lower yields with seeding rates less than 50, especially at sites with higher yield potential. Yields of field peas grown under relatively weed-free conditions should be optimized with a seeding rate of 50 to 75 seeds m-2. Key words: Pea (Pisum sativum L.), plant arrangement, row spacing, opener type, seeding rate
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".