Spatial and temporal distribution of soil inorganic nitrogen concentration in potato hills
Bibliographic record
Abstract
The purpose of this study was to determine the spatial and temporal variation in soil inorganic N concentration in the potato hill, and to discuss the implications of this variation on soil sampling strategies. The experiment was conducted in 1999 and 2000 using four treatments: bare soil with no N fertilizer applied, and a potato crop with no fertilizer N added, with 180 kg N ha -1 applied at planting, or with 120 kg N ha -1 applied at planting plus 60 kg N ha -1 applied at hilling. Elevated (above background) soil NH 4 + -N concentrations were measured for 40 or more days after planting, therefore in-season sampling should be done for both soil NO 3 − -N and NH 4 + -N. There was a period of up to 50 days between planting and rapid crop N uptake during which loss of NO 3 − -N from the root zone could occur. Split fertilizer application reduced the risk of NO 3 − -N loss during this time, but resulted in reduced tuber yield in 1999. Strong vertical variation in soil inorganic N concentration was measured in the potato hill as a result of fertilizer banding and soil N mineralization at shallow depths. Soil inorganic N concentrations were elevated in the hill, but not in the furrow, resulting in strong horizontal variation in soil inorganic N concentrations in the potato hill. Despite this variation, a systematic sampling strategy where soil was sampled in the centre of the hill, the centre of the furrow, and mid-way between the hill and furrow, done in combination with elevation control of soil sampling, resulted in an unbiased estimate of soil inorganic N concentration in the potato hill. Key words: Solanum tuberosum, nitrification, nitrate leaching, mineralization, sampling strategies
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".