Genotype and environment influence gamma aminobutyric acid concentration in short-season soybean
Bibliographic record
Abstract
Morrison, M. J., Frégeau-Reid, J. A. and Cober, E. R. 2012. Genotype and environment influence gamma aminobutyric acid concentration in short-season soybean. Can. J. Plant Sci. 92: 1093–1100. Gamma aminobutyric acid (GABA) is a four-carbon, non-structural protein found ubiquitously in life forms on the planet. In plants, it is produced in the cytosol in response to stresses, via the α-decarboxylation of glutamate by the enzyme glutamate decarboxylase. In studies, foods made from soybean (Glycine max L. Merr), with high GABA concentration, have reduced high blood pressure. Our objective was to determine if there were genotypic differences for GABA concentration among a series of short-season soybean cultivars. A historical series of 16 cultivars released from 1934 to 2000 was grown in a randomized complete block design with four replications across 3 yr at the Central Experimental Farm in Ottawa, Canada. Seed was harvested for yield and a sample taken to determine seed weight, protein, oil, L-glutamate (L-Glu) and GABA concentrations. There were significant differences among cultivars for all parameters and significant differences among years for all parameters except L-Glu. GABA was positively correlated with protein concentration, L-Glu and seed yield. There was a threefold difference in GABA concentration between the highest and lowest cultivars, but no clear relationships to weather parameters were identified. GABA concentration was determined to be moderately heritable (44%) indicating that new cultivars with higher concentrations could readily be developed. Soybean cultivars with higher GABA concentration, as part of the diet, may provide a means to reduce or prevent hypertension.
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How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".