Potato Response to a Polymer‐Coated Urea on an Irrigated, Coarse‐Textured Soil
Bibliographic record
Abstract
Controlled release fertilizers, especially polymer‐coated urea (PCU), have been shown to reduce nitrate (NO3) leaching while maintaining potato (Solanum tuberosum L.) yields, but cost has been prohibitive. A new type of PCU (Environmentally Smart Nitrogen, Agrium, Inc., Calgary, AB) is less costly than previous PCUs, but its effectiveness on potato production has not been extensively studied. A 2‐yr field study was conducted on loamy sand to evaluate the effect of this PCU on Russet Burbank tuber yield and to determine if it is economically comparable to soluble N sources. Several N rates of PCU applied at emergence were compared with two split applications of soluble N at equivalent rates. Additional treatments examined N application timing of PCU and a fertigation simulation with urea/ammonium nitrate. Petioles and midseason soil samples were collected to determine N status during the season. Overall, PCU and soluble N at equivalent N rates were found to have similar total and grade A yields and net monetary returns. The optimal N rate that resulted in maximum net returns was 251 and 236 kg N ha−1 as soluble N and PCU, respectively. Petiole NO3 concentrations were typically higher with soluble N early in the season and higher with PCU later in the season. Soil NO3 determined in samples collected in late June was found to be a better predictor of yield and potential N need than those collected in mid‐ to late July. Overall, PCU may reduce or eliminate the need for split applications of N on coarse‐textured soils.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".