Macronutrients in soil and bromegrass after long-term N fertilization
Bibliographic record
Abstract
Information on the long-term impact of repeated annual fertilizer applications of different nitrogen (N) sources on soil and plants is needed to develop sustainable grassland production systems. The concentration of macronutrients in the 0-5, 5-10, 10-15, 15-30, 30-60, 60-90 and 90-120 cm layers in a thin Black Chernozemic (Typic Boroll) soil and in bromegrass (Bromus inermis Leyss.) hay were compared after 15 annual applications of 168 and 336 kg N ha-1 as ammonium nitrate, urea, calcium nitrate, and ammonium sulphate, and a zero-N check. The concentration of NO3-N was increased by ammonium nitrate and ammonium sulphate at both N rates in most soil layers, by calcium nitrate at both N rates and by urea at 336 kg N ha-1 in the 15-60 cm soil. The accumulation of NO3-N increased with soil depth down to 60 cm, except for urea and ammonium sulphate at 168 kg N ha-1, and then it declined in deeper soil layers. The concentration of NH4-N was increased with fertilizer applications in some of the surface soil layers. The concentration of P was increased in the top 15 cm soil by ammonium nitrate and ammonium sulphate. The concentrations of Ca, Mg and K in the surface soil declined with most of the N fertilizer treatments while some treatments increased the Ca and Mg concentrations in the deeper soil layers. Increasing the N rate from 168 to 336 kg N ha-1 usually accentuated the above stated N effects on the concentration of macronutrients in the soil. The nitrate-based fertilizers caused more accumulation of NO3-N in some soil layers than the ammonium-based fertilizers. The relative increase in the concentration of NH4-N and P and the decline in the concentration of Ca, Mg and K in the soil by N addition was usually associated with the concomitant lowering of soil pH by N fertilization. In bromegrass hay, the total N concentration was increased by N fertilization but the concentration of other elements, except K, usually declined because of the dilution effect of the extra hay yield associated with N addition. Increasing the N rate from 168 to 336 kg N ha-1 further elevated the total N concentration but had no effect on the concentration of the other elements. Total N concentration in the hay tended to be greater with ammonium sulphate and ammonium nitrate than with the other 2 fertilizers. The concentration of total S was greater with ammonium sulphate than the other N fertilizers, and the concentration of P, Ca, Mg and K was not affected by the N fertilizer type. Fertilizer-induced high levels of NO3-N, NH4-N and P in soil may present potential for environmental pollution at these high N rates.
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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".