Response of Soybean [<i>Glycine max</i> (L.) Merr.] Cultivars to Genistein‐Preincubated <i>Bradyrhizobium japonicum</i>: Nodulation and Dry Matter Accumulation under Canadian Short‐Season Conditions
Bibliographic record
Abstract
The addition of genistein, a plant‐to‐bacteria signal molecule, to Bradyrhizobium japonicum cells prior to use as inocula has been shown to increase nodule number and promote soybean N2 fixation at low root zone temperatures. Previous greenhouse and field experiments involving only two cultivars have indicated that soybean [Glycine max (L.) Merr.] cultivars can vary in their response to genistein application. The objective of this study was to evaluate a range of soybean cultivars for response to genistein application under short‐season cool‐spring Canadian conditions. A 2‐year field study was conducted in 1997 and 1998 with a range of soybean cultivars recommended for Quebec. The 11 cultivars tested represented a range of yield potentials and maturity groups. They were inoculated with genistein‐preincubated B. japonicum inocula or regular inocula, applied into the furrow at the time of planting. The results of these experiments indicated that neither maturity nor yield was correlated with increases in nodulation, biomass, and plant total nitrogen content resulting from genistein treatment and that all maturity groups responded to genistein application in essentially the same way. Thus, response of soybean cultivars to genistein addition is regulated by genotype characteristics other than maturity or yield level.
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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 | 0.001 |
| 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".