Feasibility of a wider row spacing and recommended nitrogen in no‐till wheat
Bibliographic record
Abstract
Abstract The optimal row spacing aims to maximize profitability by balancing the reduction in production costs from a wider row spacing against a potential decline in yield and increased weed pressure. A wider row spacing should increase area seeded per day, improve residue flow around seeder openers and the success of seeding between stubble rows. This study investigated the feasibility of a wider row spacing by studying the effects of row spacing (25, 30, 35, 40 cm) and N fertilizer rates (20, 40, 80, 120, 160 kg N ha −1 ) on development, yield, and quality of spring wheat ( Triticum aestivum L.). The study was a two factorial in randomized complete block design. The experiment was conducted at Indian Head, SK, from 2013 to 2016. Row spacing affected plant, head, and seed density; however, the effects were generally inconsistent. One exception was biomass, which decreased as the row spacing increased in 3 of the 4 yr. Grain yield declined in 1 of the 4 yr, with the largest portion of the decrease occurring as the row spacing increased from 30 to 40 cm. As expected, increasing N rates produced greater grain yield, biomass, and grain protein. In conclusion, this study found that in most years the row spacing can be widened past 30 cm without a negative impact on grain yield in a no‐till cropping system. However, to determine the probability of a grain yield decrease as row spacing is increased, a larger study over a wider geographic region is needed.
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 | 0.000 | 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) | 0.000 | 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".