Maize Morphophysiological Responses to Intense Crowding and Low Nitrogen Availability: An Analysis and Review
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Bibliographic record
Abstract
Mounting concerns over the cost and environmental impact of N fertilizer combined with progressively higher plant densities in maize ( Zea mays L.) production systems make progress in maize N use efficiency (NUE) and N stress tolerance essential. The primary objectives of this 3‐yr field study were to (i) evaluate the N responsiveness, NUE, and N stress tolerance of multiple modern maize genotypes using suboptimal, optimal, and supraoptimal plant densities (54,000, 79,000, and 104,000 plants ha −1 , respectively) with three levels of side‐dress N (0, 165, and 330 kg N ha −1 ), (ii) identify key morphophysiological responses to the simultaneous stresses of intense crowding and low N availability, and (iii) consider our results with extensive reference to literature on maize morphophysiological responses to plant crowding and N availability. At optimal and supraoptimal plant densities, maize receiving 165 kg ha −1 of side‐dress N displayed strong N responsiveness, high NUE, pronounced crowding tolerance, and plant density independence. However, crowding tolerance was contingent on N application. Relative to less crowded, N‐fertilized environments, the 104,000 plants ha −1 , 0 kg N ha −1 treatment combination exhibited (i) reduced pre‐ and postanthesis plant height (PHT), stem diameter (SD), and total biomass; (ii) greater preflowering leaf senescence and lower R1 leaf areas at individual‐leaf, per‐plant, and canopy levels; (iii) enhanced floral protandry; (iv) lower pre‐ and postanthesis leaf‐chlorophyll content; (v) lower per‐plant kernel number (KN P ), individual kernel weight (KW), grain yield per plant (GY P ), andharvest index per plant (HI P ); and (vi) enhanced per‐plant grain yield variability (GY CV ). Genetic efforts to improve high plant density tolerance should, therefore, simultaneously focus on enhancing NUE and N stress tolerance.
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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