Response of mustard to fertilization, seeding date, and seeding rate in southern Alberta
Bibliographic record
Abstract
Yellow mustard (Sinapsis alba L.), brown mustard (Brassica juncea L.), and oriental mustard (B. juncea) have been grown in Alberta since the 1950s, but limited agronomic information specific for this crop is available. The objective of this study was to determine the response of mustard to fertilization, seeding date and seeding rate in southern Alberta. Field experiments were conducted at 20 field sites over a 4-yr period (1999–2002) under irrigated and dryland (fallow and stubble) conditions. Five experiments were conducted with the following treatments: (1) N fertilizer rate (0, 30, 60, 90 and 120 kg N ha-1), (2) urea placement (seed-placed and side-banded urea at rates of 0 to 120 kg N ha-1), (3) P fertilizer rate (0, 6.5, and 13.1 kg P ha-1), (4) S fertilizer rate (0, 10 and 20 kg S ha-1), and (5) seeding date (three dates at approximately 10-d intervals) and seeding rate (target plant densities of 75, 125, 175, 225, and 300 plants m-2). Experiment 1 was conducted with yellow mustard (AC Pennant), oriental mustard (Forge), brown mustard (Commercial Brown) and canola (Q2) (Brassica napus L.), while the remaining experiments were only conducted with yellow mustard. For maximum seed yield, mustard required 95 kg of available N Mg-1 of potential seed yield. Potential yields were closely related to available moisture, increasing 7 to 8 kg ha-1 for every mm increase in available moisture above a minimum moisture requirement of 90 mm. Seed-placed urea reduced plant stand at rates as low as 30 kg N ha-1 and reduced seed yield at rates of 60 to 120 kg N ha-1. Fourteen of 20 sites had a greater than 3% positive yield benefit due to P fertilizer. Mustard did not benefit from S fertilizer application. Delay in seeding by 3–4 wk, compared with seeding in late April to mid-May, reduced seed yield of yellow mustard by an average of 37%. Seed yield increased with seeding rate, but the maximum gain in seed yield due to high seeding rates was only 200 kg ha-1, with significant increases obtained only under very dry conditions. Early seeding and adequate N fertility were the most important agronomic practices for achieving high yields of mustard in southern Alberta. Key words: Sinapsis alba, Brassica juncea, yield, oil, nitrogen, phosphorus, sulfur, water-use efficiency
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".