Base temperature of soybean primary root elongation varies among cultivars
Bibliographic record
Abstract
Soybean ( Glycine max (L.) Merr.) is a sub-tropical crop which thrives in warm soils. In the Northern Great Plains, early spring seeding exposes soybean to cooler soil temperatures. Slower early-season development under cooler conditions may reduce competitiveness with adapted cool-season summer annual weeds, increasing yield loss risk from interference. Knowledge of critical temperature below which growth and development stops, referred to as base temperature ( Tb), could help breeders develop soybean cultivars that can extend their roots into cooler soils in early spring and compete better with weeds. Our objective was to determine the base temperature for root elongation ( TbRE) of 10 divergent, commercial soybean cultivars grown in Manitoba. Seeds of each cultivar were incubated at 25 °C for 3 days to germinate. Germinated seedlings were transferred to growth pouches. The growth pouches were placed in four growth chambers each set to a different temperature (i.e., 15, 20, 25, and 30 °C). The experiment was repeated three times. Root images were captured at the time of and every 2 days after transferring germinated seeds to the growth pouches. The x-intercept method was used to determine TbRE. There was a relatively large range in TbRE among the 10 soybean cultivars ranging from 8.1 to 13.2 °C and it was not related to the cultivar’s maturity grouping. Cultivars with lower TbRE are expected to be able to explore and occupy greater soil volume under cooler conditions. These observed result warrants further investigation in the field.
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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) | 0.000 | 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 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".