Yield response of potatoes to variable nitrogen management by landform element and in relation to petiole nitrogen – A case study
Bibliographic record
Abstract
Moulin, A. P., Cohen, Y., Alchanatis, V., Tremblay, N. and Volkmar, K. 2012. Yield response of potatoes to variable nitrogen management by landform element and in relation to petiole nitrogen – A case study. Can. J. Plant Sci. 92: 771–781. Recent increases in the cost of fertilizer N have prompted producers to assess the potential to vary inputs within fields and during the growing season to produce the highest marketable yield of potatoes (Solanum tuberosum L.). A study was conducted from 2005 to 2007 near Brandon, Manitoba, Canada, to assess the spatial variability of potato yield in upper, middle and lower landform elements on a sandy loam soil in response to a range of N fertilizer rates applied in the spring or in combination with an application during the growing season. There was no clear trend with respect to the effect of landform on potato yield. Nitrogen fertilizer increased total and marketable yield relative to the control at rates from 75 to 225 kg ha −1 in split applications or applied at seeding. No significant interaction between landform and fertilizer treatment was observed. Petiole N concentration, determined late in the growing season, was correlated with potato yield though the correlation varied considerably between years. Petiole leaflet N concentration was affected by fertilizer on most sampling dates, but decreased with time during the growing season. We conclude that although N fertilizer could be applied during the growing season based on petiole leaflet N concentration deficiencies in mid-July, there is no clear difference in potato yield due to split application relative to spring applications of N fertilizer at rates of 75 kg ha −1 or greater based on landform elements for potato production, likely due to the short growing season in western Canada.
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How this classification was reachedexpand
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 | 0.003 | 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 | 0.000 | 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 teacher head, 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".