Residual Effects of Potassium Placement and Tillage Systems for Corn on Subsequent No‐Till Soybean
Bibliographic record
Abstract
Little is known about K fertility management for no‐till (NT) soybean [ Glycine max (L.) Merr.]. This study was conducted to evaluate the residual effects of K application rate, timing, and placement for corn ( Zea mays L.) in various tillage systems on subsequent NT soybean. Field experiments involving a corn–soybean rotation were conducted from 1998 to 2000 on long‐term NT fields with medium or high exchangeable soil K levels near Kirkton and Belmont, ON, Canada. In the corn year, treatments included the combinations of three fall K rates (0, 42, and 84 kg ha −1 ), spring K rates (two rates differing by 42 kg ha −1 ), and three tillage systems [NT, zone till (ZT), and moldboard plow (CT)]. Both CT and ZT (also known as intermittent tillage systems) reduced soil K stratification relative to continuous NT. Trifoliate leaf K concentrations increased with residual fall and spring K applications in most site‐years. Average soybean yield significantly increased by 8.3% with the application of 84 kg K ha −1 in fall plus 42 to 50 kg K ha −1 in spring to previous corn only on medium‐testing (K < 100 mg L −1 ) soils. Residual tillage had no effects on leaf K or yield of NT soybean. Application of fall and spring K fertilizers to corn was equally beneficial for subsequent soybean in either continuous or intermittent NT systems. Furthermore, soil K stratification and the residual effects of tillage and K placement method were not major production issues for narrow‐row NT soybean in these growing seasons.
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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".