Sowing Season and Nitrogen Fertilization Rates in Two Oats Cultivars Grown Under Greenhouse Conditions
Bibliographic record
Abstract
Two experiments were carried out in the experimental field of the Universidade Estadual Paulista-UNESP in Ilha Solteira, São Paulo state, Brazil, in a greenhouse from April to July 2015. This study aimed at evaluating the best sowing season and response to nitrogen doses for the cultivars of yellow oat São Carlos and black IAPAR 61. The experiments were conducted in randomized blocks designs in a factorial scheme with three replicates. The sowing seasons were April 23, May 08, and May 5 and the nitrogen doses were 0; 12.5; 25; 35.5 and 50 kg ha-1 cycle. Harvests at 30 and 60 days were conducted in order to estimate of the production of dry weight (DW), crude protein (CP), neutral detergent fiber (NDF) and acid detergent fiber (ADF). For a productivity of DW, there was interaction between sowing season and oat cultivars and significant differences for CP in the second harvesting. For NDF, a significant difference was observed between harvesting. The most suitable time for sowing of both yellow oats and black oats is early May. Dry weight yield and the CP content of yellow oats increased linearly with increasing nitrogen rates while for black oats a maximum DM yield were obtained with the application of 43.5 kg ha-1 of N.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".