Dwarf sunflower response to row spacing, stand reduction, and defoliation at different growth stages
Bibliographic record
Abstract
Growth compensation of dwarf sunflower (Helianthus annuus L.) hybrids to low initial stands, later stand losses, or plant defoliation has not been reported regarding replanting decisions and crop insurance yield loss assessment. Three experiments were conducted to study the affect of stand reduction, defoliation, and row spacing on dwarf sunflower yield and quality when grown in eastern North Dakota. Experiment 1 evaluated stand reduction (0, 25, 50 and 75%) applied at growth stages (V4, R1 and R6) in 15, 45 and 76 cm spaced rows. Row spacing interactions with stand reduction and growth stage were not significant for yield indicating growth stage and stand reduction effects on yield response were independent of row spacing. In exp. 2, significant growth stage (V4, V8, R1, R2, R3, R5 and R6) by stand reduction (0, 12, 25, 37, 50, 62 and 75%) interaction showed stand reduction at vegetative growth stages not influencing yield, but as maturity progressed yield reductions became greater with increased stand reduction. Achene weight increased with increasing stand reduction at vegetative and early reproductive stages. A reciprocal relationship was noted between achene weight and achene oil content where oil content decreased as achene weight increased. Interaction of growth stage (R1 and R6) and defoliation (0, 25, 50, 75 and 100%) in exp. 3 indicated greater reduction in yield, test weight, 1000-achene weight, and achene oil conte nt as defoliatin increased at growth stage R6. Yield compensating ability of dwarf sunflower is dependent on type and level of damage and growth stage of occurrence, with total yield reduction considering all effects. Key words: Sunflower, Helianthus annuus L., row spacing, stand reduction, defoliation
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".