Early tall determinate soybean genotype E1E1e3e3e4e4dt1dt1 sets high bottom pods
Bibliographic record
Abstract
The height of bottom pods on soybean [Glycine max (L.) Merr.] plants can be a major factor affecting seed loss at harvest. Tall determinate lines have been observed to have bottom pods set higher compared with indeterminate cultivars. This study was conducted to compare bottom pod height and other agronomic characteristics of indeterminate cultivars and elite tall determinate lines. Ten indeterminate cultivars and ten tall determinate lines adapted to maturity group 00 to I were evaluated at Ottawa (45°23′N lat.) and Winchester (45°6′N lat.), Ontario, in 1996 and 1997. Bottom pods on tall determinate lines were set almost twice as high as bottom pods on indeterminate cultivars. While main stem height did not differ between the two stem types, indeterminate plants had 0.2 more main stem nodes and two additional reproductive nodes than the tall determinate lines. Tall determinate lines yielded only 90% of the indeterminate cultivars and had smaller seeds and increased lodging. These results suggest that tall determinate lines may be valuable in environments where harvesting losses result from low bottom pods, but they still require further agronomic improvement to overcome yield limitations. Key words: Soybean, determinate, pod height, Glycine max (L.) Merr.
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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 | 0.000 |
| 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".