Response of pea to rate and placement of triple superphosphate fertilizer in Alberta
Bibliographic record
Abstract
The expansion of the pea acreage on the Canadian prairies has increased the need for more information on P fertilizer response by pea to both rate and method of placement. To determine responsiveness, 52 field trials using triple superphosphate (TSP) were conducted from 1995 to 1998 over a wide range of soil types across Alberta. Five rates of 0, 6.5, 13.1, 19.6 and 26.2 kg P ha–1 were placed with the seed or in bands applied prior to seeding. The application of TSP significantly (P < 0.1) increased pea seed yield at 19 of 52 sites. The average increase in seed yield due to TSP application was 7%, with values ranging from –12 to +33% across all trials. The average yield benefit was similar in the Thin Black, Black and Gray soil zones, but was negligible in the Dark Brown soil zone and in irrigated trials. Of the 31 trials with soil test P (modified Kelowna method) levels of less than 30 kg P ha–1 to 15 cm, 52% had a significant yield increase due to application of TSP, while only one of 17 trials with soil test P levels of more than 30 kg P ha–1 had a significant yield increase. Application of 13.1 kg P ha–1 was sufficient to attain close to maximum yields in trials with soil test P levels of less than 30 kg P ha–1. The yield response of pea was insensitive to TSP placement. The mineral impact of seed placement on yield in this study was likely due to the less damaging effects of seedling growth of TSP than of the more commonly used source of P, monoammonium phosphate (MAP). Seed protein and P concentrations were not strongly affected by TSP application. Key words: Pisum sativum, phosphorus fertilizer, fertilizer placement
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 | 0.001 |
| 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 | 0.001 | 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".