Potato Response to Nitrogen Sources and Rates in an Irrigated Sandy Soil
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Management strategies to reduce N losses to the environment from potato ( Solanum tuberosum L.) production while maintaining yields depend on selecting the right N source and rate. A 5‐yr (2008‐2012) field experiment was conducted on an irrigated sandy soil in Quebec, Canada, to examine the effect of N fertilizer source and rate on total (TY) and marketable tuber yield (MY), total plant N accumulation (vines + tubers), specific gravity, culls (unmarketable tubers), and apparent fertilizer N recovery (ANR). The treatments included an unfertilized control, and three N sources [ammonium nitrate (AN), ammonium sulfate (AS), and polymer‐coated urea (PCU)] applied at four rates (60, 120, 200, and 280 kg N ha −1 ). The PCU was applied 100% at planting and the AN and AS were applied 40% at planting and 60% at hilling. The TY and MY increased with N rate up to 200 kg N ha −1 , but were similar among the N sources. On average, total plant N accumulation and ANR were greater for AN and PCU than AS. However in 2008, when there was a greater risk of N loss due to high rainfall, total plant N accumulation and ANR were greater for PCU than AN and AS. Tuber specific gravity and culls were influenced by N rate, but the response was dependent on soil and climatic conditions. Results suggest that, under humid conditions with irrigation, a one‐time application of PCU in potato production can minimize the risk of N loss without reducing tuber yield and quality.
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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 | 0.000 |
| 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 it