Gene Expression Related to Physiological Quality of Soybean Seeds
Bibliographic record
Abstract
Production of soybeans with high physiological quality is important to ensure the productivity of improved plant populations. The objective of this work was to select soybean genotypes for high physiological quality of seeds, through germination and vigor tests, and to study gene expression by transcripts and proteins. In a first trial, seeds of 12 soybean cultivars were evaluated and selected six cultivars with contrasting physiological quality levels. At the protein level, the isoenzyme systems alcohol dehydrogenase (ADH), malate dehydrogenase (MDH), phosphoglucose isomerase (PGI), sorbitol dehydrogenase (SDH), superoxide dismutase (SOD), catalase (CAT), isocitrate lyase (ICL), esterase (EST), glutamate oxaloacetate transferase (GOT), and heat-resistant proteins were evaluated. For the transcript levels, the real-time PCR technique (qRT-PCR) was used, and the genes coding for the SOD, CAT, MDH, PGI, ICL and PRX enzymes were studied. The germination and vigor tests classified the seeds of cultivars CD201, CA115 and MS8400 as high quality, while the cultivars Syn1263, Syn1279 and CD202 were classified as of low quality. The enzymes involved in the process such as dehydrogenase and phosphoglucose isomerase, are promising markers for assessing the physiological quality of soybean seeds. Higher expression of peroxiredoxin enzyme is related to the low physiological quality of soybean seeds.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".