Growth and Gas Exchange of Cucurbita pepo L. Under Nitrogen and Silicon Fertilization
Bibliographic record
Abstract
Zucchini (Cucurbita pepo L.) is a horticultural crop of great socioeconomic importance in Brazil and in the world. However, inappropriate fertilization management, such as over-fertilization of soils, may become a limiting factor for its development. Thus, the aim of this study was to evaluate the morpho-physiological behavior of zucchini submitted to nitrogen (N) doses applied via soil and foliar application of silicon (Si). The treatments were distributed in split-plot scheme in a randomized block design, with three replications. The plot was formed by silicon levels (0.0 and 6.0 g plant-1) and the subplots constituted by five nitrogen levels (30, 60, 90, 120 and 150 kg ha-1), adding up to 30 experimental units. Gas exchanges and growth parameters were assessed at 35 days after planting. The data were submitted to analysis of variance by the F test and in the cases of significance was performed a polynomial regression analysis for the nitrogen factor and Tukey test for the silicon factor. The supply of Si positively enhances the effects of N on growth characteristics and gas exchanges of zucchini. The simultaneous application of Si and N does not influence the leaf area of zucchini. The N dose of 93.9 kg ha-1 provides greater assimilation of CO2 in zucchini plants under the conditions in which the experiment was performed.
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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) | 0.001 | 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".