Potato Yield, Net Revenue and Specific Gravity Responses to Nitrogen Fertilizer under Different Canadian Agroecozones
Bibliographic record
Abstract
Applying higher nitrogen (N) rates than required for optimum potato (Solanum tuberosum L.) growth leads to economic and environmental losses. The extent to which the N rate associated with maximum potato yields differs from that maximizing net revenue (NR) or potato specific gravity is not fully understood. The objectives of this three-year study (2013–2015) conducted at five sites in three Canadian provinces (MB-1; MB-2; QC-1; QC-2; PEI) (15 site-years) were to: (i) assess potato marketable yield, NR, and specific gravity responses to increasing N application; (ii) calculate the N rate maximizing marketable (Nmax) yield and NR using different statistical models. The year, N fertilizer, and their interaction were significant on marketable yield and NR except at the MB-1 site where no significant effect of N was observed. No significant yield increases were observed at a N rate above 60 kg N ha−1 at four site-years and above 120 kg N ha−1 at five site-years, implying that the current recommended N rate could be reduced. All models fitted the marketable and NR data equally based on R2, mean bias error or root mean square error and resulted in comparable predicted yield and NR values. However, Nmax values were different depending on the model with higher values being predicted by the quadratic- (161.4 to 191.9 kg N ha−1) and the quadratic plateau models (60 to 191.9 kg N ha−1), while lower Nmax values were obtained with linear plateau- (60.6 to 129.8 kg N ha−1) and Mitscherlich–Baule plateau models (60.9 to 130. 9 kg N ha−1). Nitrogen rate maximizing NR was on average 4% lower than the N rate maximizing marketable yields, except at one site where it was higher by 26 kg N ha−1 when the quadratic plus plateau model was used. Specific gravity tended to decrease with the N rate. Our study confirms trade-offs between the N rate maximizing yields or NR with that maximizing specific gravity. Nitrogen rate maximizing marketable yield and NR varies depending on the selected model.
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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 | 0.000 | 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 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".