Pre‐Sidedress Nitrate Test and Other Crop‐Based Indicators for Fresh Market and Processing Sweet Corn
Bibliographic record
Abstract
Commercial sweet corn ( Zea mays L.) production requires significant quantities of fertilizer N, leading to inefficient N use and negative environmental impact. A field experiment was conducted for 4 yr (2001–2004) in Ottawa, Canada, to assess and compare presidedress soil nitrate test (PSNT) with some crop‐based measurements (canopy reflectance, leaf chlorophyll and plant total N) for improved N management. A fresh market sweet corn (FMSC, hybrid ‘Temptation’) grown from 2001 to 2003, and a processing sweet corn (PSC, hybrid ‘Hollywood’) from 2002 to 2004, both received five fertilizer N rates (0, 50, 100, 150, and 200 kg N ha −1 ). Soil samples taken from the V4 to V8 growth stages were analyzed for NO 3 − –N. Leaf chlorophyll content (SPAD) and canopy reflectance were also measured for FMSC at the same time. All N treatments affected the number of marketable ears, kernel dry weight and total biomass production. However, in most cases, there was no difference between N treatments from 100 to 200 kg ha −1 . The PSNT NO 3 − –N increased linearly with the fertilizer N rates, and there were significant positive correlations between PSNT at V4 to V6 and the number of marketable ears. It was evident that PSNT, plant N concentration at V6, SPAD and canopy reflectance all differentiated sweet corn N response similarly, and they were highly correlated with one another. We concluded that PSNT at V4 to V6 was effective in predicting sweet corn N requirement in this cool and short‐growing region.
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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 | 0.001 | 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 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".