Assessment of Plant‐Available Potassium for No‐Till, Rainfed Soybean
Bibliographic record
Abstract
Temporal and spatial availability of K can influence soybean [ Glycine max (L.) Merr.] productivity. This study quantified the impact of initial soil K concentrations, soil‐water content, and soybean K uptake on soil K pools (water‐extractable solution‐phase K [K sol ], 1 mol L −1 NH 4 OAc‐extractable K, referred to as exchangeable K (K exch ), and 5‐min sodium tetraphenylboron [NaTPB] extractable K [K TPB ]) and compared predictions of plant K availability using the NaTPB vs. NH 4 OAc tests. Soil and soybean samples were collected five times between the VE and R6 development stages in 2003 and 2004 from fallow and cropped no‐till Toronto–Millbrook silt loam Alfisols at the Throckmorton Purdue Agricultural Center. Gravimetric soil water content was measured weekly during the growing season. Low‐, medium‐, and high‐K fertility plots were replicated four times. Initial K exch levels ranged from 60 to 290 and from 50 to 90 mg kg −1 at the 0‐ to 10‐ and 10‐ to 20‐cm depths, respectively. Medium‐ and high‐fertility soils had the highest grain yields. The 0‐ to 5‐cm soil layer had the highest K exch levels, water availability, and soybean K uptake. Compared with K exch, K sol levels were less stratified and the surface layer was less dynamic. The NaTPB extraction was a better predictor of soybean K uptake in 1 yr, but across both years, NH 4 OAc was superior. Potassium measurements in the 0‐ to 10‐cm soil layer provided slightly better estimates of plant K uptake than those in the 0‐ to 20‐cm layer. Greater water availability and K uptake in the 0‐ to 5‐cm soil layer suggest that under evenly distributed, intermittent rainfall conditions in somewhat poorly drained soils, vertical soil K stratification might not be a concern for no‐till soybean production.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".