IMPACT OF SORBITOL- INDUCED OSMOTIC STRESS ON SOME BIOCHEMICAL TRAITS OF POTATO IN VITRO
Bibliographic record
Abstract
This study had as principal objective identification of osmotic-tolerant potato genotypes by using "in vitro" tissue culture and sorbitol as a stimulating agent, to induce water stress, which was added to the culture nutritive medium in different concentration (0,50, 110, 220, 330 and 440 mM). The starting point was represented by plantlets culture collection, belonging to eleven potato genotypes: Barcelona, Nectar, Alison, Jelly, Malice, Nazca, Toronto, Farida, Fabulla, Colomba and Spunta. Plantlets were multiplied between two internodes to obtain microcuttings (in sterile condition), which were inoculated on medium. Sorbitol-induced osmotic stress caused a significant reduction in the ascorbic acid, while the concentration of proline, H2O2 and solutes leakage increased compared with the control. Increased the proline content prevented lipid peroxidation, which played a pivotal role in the maintenance of membrane integrity under osmotic stress conditions. The extent of the cytoplasmic membrane damage depends on osmotic stress severity and the genotypic variation in the maintenance of membranes stability was highly associated with the ability of producing more amounts of osmoprotectants (proline) and the non-enzymic antioxidant ascorbic acid in response to osmotic stress level. The results showed that the genotypes Jelly, Nectar, Allison, Toronto, and Colomba are classified as highly osmotic stress tolerant genotypes, while the genotypes Nazca and Farida are classified as osmotic stress susceptible ones.
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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) | 0.001 | 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".