Relationship between asparagine metabolism and protein concentration in soybean seed
Bibliographic record
Abstract
The relationship between asparagine metabolism and protein concentration was investigated in soybean seed. Phenotyping of a population of recombinant inbred lines adapted to Illinois confirmed a positive correlation between free asparagine levels in developing seeds and protein concentration at maturity. Analysis of a second population of recombinant inbred lines adapted to Ontario associated the elevated free asparagine trait with two of four quantitative trait loci determining population variation for protein concentration, including a major one on chromosome 20 (linkage group I) which has been reported in multiple populations. In the seed coat, levels of asparagine synthetase were high at 50 mg and progressively declined until 150 mg seed weight, suggesting that nitrogenous assimilates are pre-conditioned at early developmental stages to enable a high concentration of asparagine in the embryo. The levels of asparaginase B1 showed an opposite pattern, being low at 50 mg and progressively increased until 150 mg, coinciding with an active phase of storage reserve accumulation. In a pair of genetically related cultivars, ∼2-fold higher levels of asparaginase B1 protein and activity in seed coat, were associated with high protein concentration, reflecting enhanced flux of nitrogen. Transcript expression analyses attributed this difference to a specific asparaginase gene, ASPGB1a. These results contribute to our understanding of the processes determining protein concentration in soybean seed.
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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".