Effects of maturity group and stem growth habit on the branching plasticity of soybean cultivars grown at various planting densities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To elucidate the effects of maturity and the stem growth habit on the planting density-dependent branching plasticity of soybean cultivars, we studied the branch traits of 12 cultivars or lines planted at different densities (8.3, 16.7, and 22.2 plants m−2) in Sapporo (2012) and Ebetsu (2013). The 12 cultivars and lines consisted of three determinate cultivars from Hokkaido, three indeterminate cultivars from the northern US, and near-isogenic lines with the backgrounds of Canadian, US, and Japanese cultivars exhibiting diverse stem growth habits. We investigated the relationship between the maturity or stem growth habit and branching plasticity, which was calculated based on the ratios of different branch traits under sparse and dense planting conditions. The use of the ratios of the total branch length and the number of nodes per branch under sparse and dense planting conditions as a measure of branching plasticity revealed varietal differences across years. For the determinate and indeterminate cultivars in both years, branching plasticity was positively correlated with the number of days until stage R5 (onset of seed filling), which is when branches cease to elongate. Comparisons of Japanese and US cultivars and near-isogenic lines for the Dt1 gene (mediating the stem growth habit) indicated that the branching plasticity of indeterminate cultivars and lines is greater than that of determinate cultivars, with a large variation among backgrounds and cultivars. The results of this study imply that branching plasticity is greater in late-maturing soybean cultivars. Moreover, the indeterminate growth habit substantially enhances branching plasticity.
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.
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 | 0.000 | 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) | 0.000 | 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 it