Predicting nitrogen fertilizer requirements of potatoes in Atlantic Canada with soil nitrate determinations
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Bibliographic record
Abstract
Nitrogen greatly affects potato ( Solanum tuberosum L.) yield, but excess N can result in environmental degradation. In this study soil nitrate (NO 3 -N) content was determined pre-plant to predict fertilizer N requirements of potatoes in Atlantic Canada and in mid-season to adjust N fertilization during the growing season. Soil NO 3 -N contents were measured to a 0.30-m depth in spring prior to planting at four on-farm sites in each of 3 yr (1995 to 1997) in the upper St. John River Valley of New Brunswick, Canada. Mid-season soil NO 3 -N contents at a 0–0.30 m depth were also determined (32–47 days after planting) at two sites in three N treatments in 1995 (0, 50, and 250 kg N ha -1 ) and in four N treatments in 1996 and 1997 (0, 50, 100, and 250 kg N ha -1 ). The yield response of potatoes to six rates of N fertilization (0–250 kg N ha -1 ) with and without supplemental irrigation was used to determine the economically optimum N application (Nop). The pre-plant spring soil NO 3 -N test alone could not adequately predict the N requirements of potatoes in Atlantic Canada; the Nop and relative yield were poorly correlated (0.07 < R 2 < 0.52) with spring soil NO 3 -N content. The mid-season soil NO 3 -N test, however, could be used to determine the need for supplemental N fertilizer; NO 3 -N content correlated well (0.44 < R 2 < 0.68) with the relative yield for total and marketable yield. We suggest a critical mid-season value of 80 mg NO 3 -N kg -1 soil for marketable yield, above which additional N application might not be necessary. Key Words: N fertilizer, nitrate, Nop, relative yield, Solanum tuberosum, critical value
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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