Induction of Phytoalexins Gliceoline and Proteins Related to Defense in Soybean Cotyledon Treated With Yeast
Bibliographic record
Abstract
Yeasts can induce mechanisms of plant resistance due to compounds with eliciting characteristics, so the aim of this work was to evaluate the effect of yeast on the induction of phytoalexins gliceoline, peroxidase, polyphenoloxidase and phenylalanine ammonia-lyase from soy cotyledons. To determine the defense enzymes, soybean seeds were sown and the cotyledons treated with sterile distilled water, Cryptococcus laurentii (AH 03-1), Pichia guilliermondii (AH 16-2), Rhodotorula glutinis (AH 14-3), Sporidiobolus johnsonii (AH 16-1) and Zygoascus hellenicus (AH 14-1). Biochemical analyzes of the formation of phytoalexins and the activity of the enzymes peroxidase, polyphenoloxidase, phenylalanine ammonia-lyase and total proteins were performed. For phytoalexins glycerolins the yeasts Cryptococcus laurentii (AH 03-1) and Zygoascus hellenicus (AH 14-1) promoted an increase of 83.65% and 78.75% in the formation of this compound. Cryptococcus laurentii (AH 03-1) increased peroxidase activity by 36.84%, while for polyphenoloxidase, the Pichiaguilliermondii e yeasts (AH 16-2), Rhodotorula glutinis (AH 14-3), Sporidiobolus johnsonii (AH 16-1) and Zygoascus hellenicus (AH 14-1), increased the activity of this enzyme by 33.33%, 28.00%, 33.33% and 33.33%, respectively. For phenylalanine ammonia-lyase, Cryptococcus laurentii (AH 03-1) and Zygoascushellenicus (AH 14-1) promoted an increase of 75.57% and 78.86%, respectively, in their activity. The results demonstrate the potential of yeasts studied in the induction of phytoalexins glyceolins and in the activity of peroxidase, polyphenoloxidase and phenylalanine ammonia-lyase in soybean cotyledons.
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 | 0.000 | 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) | 0.001 | 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".