Agronomic Performance of Sunflower Hybrids in the Mid-Northern Region of Mato Grosso, Brazil
Bibliographic record
Abstract
Helianthus annus L. belongs to the family Asteraceae, with a yearly cycle and high adaptability rate to different climate conditions. Its culture was boosted by the production of animal feed, oil extraction for humans or for biodiesel, ornamentation and bird feed. The agronomic performance of sunflower genotypes in the Mid-Northern region of the State of Mato Grosso, Brazil, was assessed. Data for the production and industrial sectors will be thus provided for the selection of genotypes with the best agronomic traits when cultivated in the region. Current study was performed at the Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso, on the Campus Campo Novo do Parecis MT Brazil, during 2018. Eight genotypes were evaluated in assays with randomized blocks and four replications. Evaluated traits comprised days for initial florescence, plant height, stalk diameter, green and dry mass, days for physiological maturity, mean diameter of the head, mass of head and achenes per head, both necessary to obtain achene:head ratio, mass of one thousand achenes, number of achenes per head and productivity of achenes of the oil. Genotypes with high grain yield tended towards greater size and cycle. Genotypes SYN 045, BRS 323 and MULTISSOL had good grain productivity plus good production of green and dry mass. The first two genotypes had an oil rate above 40%, with good oil productivity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".