Influence of population density, row spacing and hybrid on forage corn yield and nutritive value in a cool-season environment
Bibliographic record
Abstract
Increasing yield for silage and grazing in cool, short-season areas may be possible by planting corn (Zea mays L.) at high population densities and at narrow row spacing. The objective was to determine how population density (75 000, 100 000, and 125 000 plants ha -1 ) and row spacing (standard: 76 cm and narrow: 38 cm) affected whole-plant yield, yield-related parameters, and nutritive value of two corn hybrids grown at Brooks and Lacombe, Alberta during 2 yr. The hybrids (Pioneer 39F45 and 39N03) were rated at 2000 Ontario corn heat units (CHU). Trial, hybrid, population density and row spacing interacted to influence whole-plant yield. Population density had a greater impact on whole-plant yield than row spacing and hybrid choice. Generally, yield leveled off at 100 000 plants ha -1 when the interaction of all effects was considered. Leaf area index (LAI) and whole-plant yield at this density were 2.68 and 12.0 Mg ha -1 , respectively. Narrow compared with standard row spacing had positive effects on whole-plant yield of one hybrid, but not the other and improved LAI at 75 000 plants ha -1 , but not at the other plant densities. Increasing plant density and reducing row spacing had only minor effects on whole-plant nutritive value. Growing corn in narrow rows to accommodate prevalent planting equipment should have no adverse effects on whole-plant corn production in short-season areas of Canada. However, when considering changes in corn management to maximize whole-plant yield narrow row spacing is not as important as achieving a plant density of approximately 100 000 plants ha -1 . Key words: Corn, Zea mays L., nutritive value, population density, row width, silage yield
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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) | 0.000 | 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".