Potential of Corn as Forage on Alfisol and Vertisol Soil in Agrosilvopastural System with Kayuputih (Melaleuca leucadendron Linn)
Bibliographic record
Abstract
This research was aimed to know the morphologic and physiologic characteristics and corn plant production as forage on alfisol and vertisol soil at Kayuputih intercropping system. Supporting forage supply is one of goals in forest for food/feed program, and it significantly showed at Kayuputih (Melaleuca leucadendron Linn) intercropping system. Kayuputih intercropping system of corn was planted particularly at the 3rd rotation (May-July). The research performed by a strip plot design, soil type was the main plot, and the interface zone (IZ) was the secondary plot. Interface zone was 1 m (IZ-1), 2 m (IZ-2), and 3 m (IZ-3) distance from the Kayuputih plantation row. Growth and physiologic data was analyzed using Bartlette to obtain data homogenity, followed by analysis of variance and DMRT at 5% degree of confidence, data transformation was performed when needed. Contrast orthogonal (5%) test was used to do the grouping based on soil type. Biplot technique as a development from the multivariate technique was performed to determine the stability of IZ treatment toward result. Forage potency on alfisol was higher (5.04 ton/ha) than on vertisol (4.04 ton/ha). Interaction between the IZ and soil type was found at several variables: number of stomata, stomatal aperture width, proline content, plant growth rate on 3-6 wap, net assimilation rate on 3-6 wap, fresh root weight on 3 wap, root dry weight on 3 wap, fresh canopy weight on 6 wap and canopy dry weight on 6 wap. The highest level of corn forage production was IZ-3 on alfisol soil (1.26 ton/ha) and the lowest production was IZ-1 on vertisol soil (0.73 ton/ha).
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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) | 0.000 | 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 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".