Row Arrangements of Maize and Soybean Intercrop on Silage Quality and Grain Yield
Bibliographic record
Abstract
The success of maize + soybean intercrop depends on the plant arrangement. An experiment was carried out to evaluate different row arrangements on intercrop forage yield, silage quality and maize grain yield in relation to maize as a sole crop. The experiment was set up with a randomized complete block design with eight row arrangements between maize and Soybean. Maize biomass yield among crop arrangements were similar, although, lower than the maize sole crop. On the other hand, these treatments showed higher soybean biomass yield, which in turn increased silage crude protein and crude protein yield per unit area. Maize thousand grain weight, grain yield per plant and per area was affected by the intercrop arrangements. The use of two corn rows + two soybean rows (2M+2S-30 cm) and four corn rows + four soybean rows (4M+4S-30 cm) showed higher crude protein yield per area associated with similar maize grain yield in relation to the sole maize crop. In conclusion, alternating four maize rows with four soybean rows was the optimum row ratio in maize + soybean intercrop, though this needs to be further confirmed by more trials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".