Effects of Levels of Growth Regulator and Application Periods in Maize Genotypes on the Agronomic Traits
Bibliographic record
Abstract
The objective of this study was to evaluate the agronomic characteristics of corn hybrids short cycle on levels of plant regulator Stimulate® in two periods. The planting was done in field, in the experimental farm of the Mato Grosso do Sul State University. The experimental design was completely randomized, in a factorial scheme (3 × 2 × 2), with four replicates. The treatments consisted of three levels (0, 250 and 500 mL ha-1) of the plant regulator, with two hybrids (30A37PW Morgan and P3646-HY) and two times of application (vegetative stage and reproductive stage). The following averages were evaluated: plant height, number of leaves, tassel weight, tang weight, tang length, leaf weight, number of spikes, stem weight, stem diameter, ear diameter and whole plant weight. The number of leaves, number of spikes and stalk diameter were higher to P3646-HY and the tassel weight was higher to Morgan 30A37PW. The application of growth regulator of the doses of 250 and 500 mL ha-1, divided in the vegetative and reproductive stages, caused a reduction in stem diameter and whole plant weight, and in the other parameters the application in single dose and in divided dose did not affect plant growth. The genotype P3646-HY obtained higher number of leaves, number of spikes and stem diameter than the genotype 30A37PW Morgan, but this presented higher tassel weight.
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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 | 0.001 |
| 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".