Genetic variation for physiological traits affecting drought tolerance among Ontario-adapted commercial soybean [Glycine max (L.) Merr.] varieties grown in 1-m rooting columns
Bibliographic record
Abstract
Drought stress significantly limits soybean production in Ontario. Identification of physiological traits to improve drought tolerance in soybean would benefit from controlled-environment phenotyping methods. It was hypothesized that elite Ontario-adapted soybean varieties would differ for drought tolerance. A greenhouse culture system was developed employing 1-m rooting columns filled with amended field soil, that presents field-like volumetric soil water content and rooting profiles by depth. Different levels of drought stress were simulated in this system by restoring soil water to 100% (control), 75% (mild stress) or 50% (drought stress) of the maximum soil water holding capacity by daily weighing and watering from first flower (R1) until maturity. The effect of applying fertilizer throughout the 1-m soil profile instead of confining it to the upper 30 cm was tested. Distributing fertilizer over the entire 1-m rooting depth resulted in deeper rooting and more soil water extraction at depth at the R1 stage; however, these effects did not persist until maturity and so did not affect drought tolerance. Fifteen Ontario-adapted commercial soybean varieties were compared for their drought tolerance, defined as the ratio of their seed yield under drought conditions compared to control conditions (seed yield ratio; SYR). Similar to the effects of drought in the field, pod number was by far the yield component most affected, with effects on seeds per pod and single-seed weight being relatively minor. Based on their SYR, two drought-sensitive varieties (Saska and OAC Drayton) and three drought-tolerant varieties (OAC Lakeview, OAC Champion, and PRO 2715R) were identified. Principal components analysis showed that drought-tolerant varieties were those that maintained relatively high water use, shoot dry matter, and pod number under stress. Varieties differed for root biomass distribution by depth, but not for soil water extraction profiles, and there was no evidence that differences in drought tolerance were associated with rooting traits among these fifteen varieties. This study helps define the physiological basis of soybean variety differences in drought tolerance, and provides novel phenotyping tools for soybean breeders to select for root function and yield formation traits that could improve soybean yield under drought stress.
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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".