Response of a Leafy and Non‐Leafy Maize Hybrid to Population Densities and Fertilizer Nitrogen Levels
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Bibliographic record
Abstract
Optimum plant population density (PPD) of maize ( Zea mays L.) for grain and/or silage production depends on hybrid type, soil fertility and agronomic management. Limited information exists on the yield response of Leafy maize hybrids to different PPD under varying N application rates. A field study was conducted during 2003 and 2004 in Ottawa, Canada to evaluate grain and silage yields of a Leafy hybrid (‘Maizex LF850 RR’) with a conventional hybrid (‘Pioneer 3893’), under three PPD (60 000, 75 000, and 90 000 plants ha −1 ) and four N fertilizer (0, 75, 150, and 225 kg N ha −1 ) regimes. Canopy light interception, plant dry matter (DM), silage, and grain yield were measured. The Leafy hybrid had 20 to 25% more leaf area, on an individual plant basis, and produced significantly greater silage DM (21.1 vs. 20.0 Mg ha −1 ), but had a significantly smaller grain yield (9.4 Mg ha −1 ) than the conventional hybrid (9.7 Mg ha −1 ). The Leafy hybrid was more sensitive to high density and low N stresses, resulting in more barren plants (up to 15%), lower harvest index (HI), thus significantly lower grain yield than the conventional hybrid in 2003. Grain yield reached to a maximum with 225 kg N ha −1 followed by 75 and 150 kg N ha −1 , but silage DM was not different between 150 and 225 kg N ha −1 Plant population density had no effect on grain yield but silage yield increased linearly as PPD increased from 60 000 to 90 000 plants ha −1 Within the tested range of PPD, no differential response of hybrids was observed in terms of grain yield or silage DM, and N treatments had no effect on response of hybrids to PPD. We conclude that the Leafy hybrid was more sensitive to high PPD and low N stresses than the conventional hybrid especially for grain production. The optimum PPD for silage production may be beyond 90 000 plants ha −1 for both types of hybrids.
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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 | 0.000 |
| 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 it