Optimum seeding date and rate for irrigated cereal and oilseed crops in southern Alberta
Bibliographic record
Abstract
McKenzie, R. H., Bremer, E., Middleton, A. B., Pfiffner, P. G. and Woods, S. A. 2011. Optimum seeding date and rate for irrigated cereal and oilseed crops in southern Alberta. Can. J. Plant Sci. 91: 293–303. High crop productivity is essential for irrigated crops and may be strongly affected by decisions of seeding date and rate. An irrigated field experiment was conducted at two locations in southern Alberta for 4 yr to compare the impact of seeding date and rate on productivity and quality of nine cereal crops and two oilseed crops. Seeding rate was only evaluated on one date in late April or early May, when maximum yields were expected. Delayed seeding reduced crop yields by 0.6 to 1.7% per day after the end of April: flax (Linum usitatissimum L.) ≤ CWRS wheat (Triticum aestivum L.), feed triticale (×Triticosecale W.) ≤ CPS or SWS wheat ≤ triticale or barley (Hordeum vulgare L.) silage ≤ durum (T. turgidum L.), feed or malt barley < canola (Brassica napus L.). Crop quality deteriorated with delayed seeding for some crops, particularly canola, malt barley and SWS wheat, but was unaffected or even slightly improved for other crops. Seeding rate generally had a smaller effect on crop yield or quality than seeding date, but triticale and SWS wheat required high seeding rates to achieve maximum yields. Early seeding and a sufficient seeding rate were required for high crop productivity of irrigated cereal and oilseed crops in southern Alberta.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".