Plant Density Effect on Silage Yield of Maize Cultivars
Bibliographic record
Abstract
<p>In order to study of plant density effect on silage yield of new maize hybrids an experiment was conducted in factorial on the basis of randomized completely block design with four replications at agricultural research station in Qarakheil (Qaemshahr) in 2014 in Iran, after wheat harvesting. New hybrids are SC703 and SC705 that were compared with SC704. Four densities were 75,000, 85,000, 95,000 and 105,000 plant per hectar. Eeach plant planted in four rows with intera-row spacing of 75 cm. Silage yield, plant height, ear height, kernel number in ear row, kernel row number,dry silage yield, kernel, stem and leaves protein were measured. Result showed that SC704 had the highest silage yield with 70.96 t/ha. SC705 and SC703 had 64.67 and 60.22 t/ha silage yield. Density of 105,000 and 95,000 plant per hectar had higher silage yields in compare of other densities with 67.04 and 66.20 t/ha respectively. Result showed that SC704 had the highest dry silage yield with 43.19 t/ha. SC705 and SC703 had 38.69 and 36.75 t/ha dry silage yield respectively. Density of 105,000 and 95,000 plant per hectar had higher dry silage yields in compare of other densities with 40.67 and 40.55 t/ha respectively. With increasing of density, crude protein (in kernel, stem and leaves) decreased.</p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 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".