Genotypic Variation for Three Physiological Traits Affecting Drought Tolerance in Soybean
Bibliographic record
Abstract
ABSTRACT Three physiological traits that may affect performance of soybean [Glycine max (L.) Merr.] when soil water availability is limiting are (i) water use efficiency (WUE), (ii) regulation of whole plant water use in response to soil water content, and (iii) leaf epidermal conductance (ge) when stomata are closed. Six soybean plant introductions (PIs), eight breeding lines derived from them, and nine cultivars were compared for variability in these three traits during vegetative growth in two greenhouse studies. In the first experiment, whole plant water use, normalized both to plant size and evaporative demand (the normalized transpiration ratio, NTR), was monitored during a 10‐d cycle of gradually increasing drought stress and then for an additional 2 d following rewatering. The critical soil water content at which each plant began to reduce its water use (FTSWC), was determined. The WUE was estimated as the ratio of total plant dry weight to total water used. In the second experiment, ge was determined for these same 23 genotypes by measuring leaf water vapor exchange after a 36‐h dark adaptation. Substantial variation was found among genotypes for WUE, FTSWC, ge, and also the extent to which NTR recovered on rewatering. Generally, adapted cultivars had greater WUE and lower ge than did PIs. However, PI 471938 and its progeny N98‐7264 were clear exceptions to this trend. An unexpected finding was that WUE was significantly negatively correlated with ge across genotypes.
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 | 0.001 | 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".