The Effect of Formulation and Amount of Potassium Fertilizer on Macromineral Concentration and Cation-Anion Difference in Tall Fescue
Bibliographic record
Abstract
This study investigated the feasibility of altering the dietary cation-anion difference (DCAD) in grass by altering the grass variety and the amount and formulation of K fertilizer application. In experiment 1, treatments were combinations of 2 varieties (Barcel and Hi-Mag) of tall fescue (Festuca arundinacea Schreb); 2 rates of K (0 and 250 kg/ha), supplied as KCl; and 2 rates of Mg (0 and 60 kg/ha), supplied as MgO. In experiment 2, K fertilizer was applied at 0 or 125 kg/ha as KCl or K2SO4. There was no difference between HiMag and Barcel tall fescue in the concentrations of Mg, S, and Cl. Application of K fertilizer decreased concentrations of Mg, but the magnitude of the decrease was not consistent across harvests. Conversely, application of Mg fertilizer increased Mg concentrations, but again, the magnitude of the increase was not consistent across harvests. The concentrations of Ca were higher in HiMag than in Barcel tall fescue, with the magnitude of the difference increasing from first to last harvest. Potassium fertilizer decreased Ca concentrations in the first, fourth, and fifth harvests only. Calcium concentration was decreased by a greater magnitude in HiMag tall fescue as a result of Mg fertilization. The HiMag tall fescue contained lower concentrations of K than did Barcel tall fescue in the first, second, and third harvests. Application of K fertilizer increased the K concentration in all 5 harvests but did not affect Na concentrations except in the last harvest. The HiMag tall fescue contained less Na than did Barcel, but the magnitude of the difference was affected by K and Mg fertilization. Application of K fertilizer decreased S concentrations in first-harvest grass, increased concentrations in second-and third-harvest grasses, and had no effect in fourth-or fifth-harvest grasses. Application of Mg fertilizer decreased S concentrations of tall fescue. Application of K fertilizer increased DCAD values for grass harvested from the second through fifth harvests. The increase in DCAD attributable to K fertilizer was less in HiMag than in Barcel tall fescue. Application of K fertilizer as K2SO4 increased dry matter yield and S concentrations of HiMag tall fescue, whereas K applied as KCl increased concentrations of K and Cl. There was no effect of fertilizer formulation on Na concentrations. The DCAD was lower in HiMag tall fescue fertilized with K2SO4 compared with that fertilized with KCl. This study showed that DCAD of grass can be manipulated by the choice of grass variety, fertilizer formulation, and fertilizer application rate.
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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 | 0.000 |
| 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 | 0.001 | 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 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".